Complete List of Works

@article{info:hdl:2013/321123,

title = {The CLAIRE COVID-19 initiative: approach, experiences and recommendations},

author = {Gianluca Bontempi and Ricardo Chavarriaga and Hans eD Canck and Emanuela Girardi and Holger H Hoos and Iarla Kilbane-Dawe and Tonio Ball and Ann Nowe and Jose Sousa and Davide Bacciu and Marco Aldinucci and Manlio eD Domenico and Alessandro Saffiotti and Marco Maratea},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/321123/3/Bontempi2021_Article_TheCLAIRECOVID-19InitiativeApp-2.pdf},

year  = {2021},

date = {2021-01-01},

journal = {Ethics and information technology},

abstract = {A volunteer effort by Artificial Intelligence (AI) researchers has shown it can deliver significant research outcomes rapidly to help tackle COVID-19. Within two months, CLAIRE's self-organising volunteers delivered the World's first comprehensive curated repository of COVID-19-related datasets useful for drug-repurposing, drafted review papers on the role CT/X-ray scan analysis and robotics could play, and progressed research in other areas. Given the pace required and nature of voluntary efforts, the teams faced a number of challenges. These offer insights in how better to prepare for future volunteer scientific efforts and large scale, data-dependent AI collaborations in general. We offer seven recommendations on how to best leverage such efforts and collaborations in the context of managing future crises.},

note = {DOI: 10.1007/s10676-020-09567-7},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/322517,

title = {A tutorial on network-wide multi-horizon traffic forecasting with deep learning},

author = {Giovanni Buroni and Gianluca Bontempi and Karl Determe},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/322517/3/EasyChair-Preprint-4944.pdf},

year  = {2021},

date = {2021-01-01},

journal = {CEUR Workshop Proceedings},

volume = {2841},

abstract = {Traffic flow forecasting is fundamental to today's Intelligent Transportation Systems (ITS). It involves the task of learning traffic complex dynamics in order to predict future conditions. This is particularly challenging when it comes to predict the traffic status for multiple horizons into the future and at the same time for the entire transportation network. In this context deep learning models have recently shown promising results. This models can inherently capture the non-linear space-temporal correlations (ST) in traffic by taking advantage of the huge volume of data available. In this study the authors present a LSTM encoder-decoder for multi-horizon traffic flow predictions. We adopted a direct approach in which the model simultaneously predict traffic conditions for the entire Belgian motorway transport network at each time step. The results clearly show the superiority of this model when compared with other deep learning models. In the workshop, conference attendees will learn how to process and visualize mobility data, obtain optimal features for traffic flow forecasting, build a LSTM encoder-decoder and perform predictions in an online manner.},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/325214,

title = {Contrastive self-supervised clustering of scRNA-seq data.},

author = {Madalina Ciortan and Matthieu Defrance},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/325214/1/doi_308858.pdf},

year  = {2021},

date = {2021-01-01},

journal = {BMC bioinformatics},

volume = {22},

number = {1},

pages = {280},

abstract = {Single-cell RNA sequencing (scRNA-seq) has emerged has a main strategy to study transcriptional activity at the cellular level. Clustering analysis is routinely performed on scRNA-seq data to explore, recognize or discover underlying cell identities. The high dimensionality of scRNA-seq data and its significant sparsity accentuated by frequent dropout events, introducing false zero count observations, make the clustering analysis computationally challenging. Even though multiple scRNA-seq clustering techniques have been proposed, there is no consensus on the best performing approach. On a parallel research track, self-supervised contrastive learning recently achieved state-of-the-art results on images clustering and, subsequently, image classification.},

note = {DOI: 10.1186/s12859-021-04210-8},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/331277,

title = {DOME: recommendations for supervised machine learning validation in biology},

author = {Ian Walsh and Dmytro Fishman and Dario Garcia-Gasulla and Tiina Titma and Gianluca Pollastri and Emidio Capriotti and Rita RC Casadio and Salvador Capella-Gutierrez and Davide Cirillo and Alessio Del Conte and Alexandros A. C. Dimopoulos and Victoria Dominguez Del Angel and Joaquin Dopazo and Piero Fariselli and José Maria Fernández and Florian Huber and Anna Kreshuk and Tom Lenaerts and Pier Luigi Martelli and Arcadi Navarro and Pilib Broin and Janet Pi nero and Damiano Piovesan and Martin Reczko and Francesco Ronzano and Venkata Satagopam and Castrense Savojardo and Vojtěch Spiwok and Marco Antonio Tangaro and Giacomo Tartari and David Salgado and Alfonso Valencia and Federico Zambelli and Jennifer Harrow and Fotis F. E. Psomopoulos and Silvio S. C. E. Tosatto},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/331277},

year  = {2021},

date = {2021-01-01},

journal = {Nature methods},

note = {DOI: 10.1038/s41592-021-01205-4},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/334299,

title = {TIGER: The gene expression regulatory variation landscape of human pancreatic islets.},

author = {Lorena Alonso and Anthony Piron and Ignasi Morán and Marta Guindo-Martínez and Sílvia Bon`as-Guarch and Goutham Atla and Irene Miguel-Escalada and Romina Royo and Montserrat Puiggr`os and Xavier Garcia-Hurtado and Mara Suleiman and Lorella Marselli and Jonathan L S Esguerra and Jean Valéry Turatsinze and Jason M Torres and Vibe Nylander and Ji Chen and Lena Eliasson and Matthieu Defrance and Ramon Amela and MAGIC and Hindrik Mulder and Anna L Gloyn and Leif Groop and Piero Marchetti and Decio L. Eizirik and Jorge Ferrer and Josep JM Mercader and Miriam Cnop and David Torrents},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/334299},

year  = {2021},

date = {2021-01-01},

journal = {Cell reports},

volume = {37},

number = {2},

pages = {109807},

note = {DOI: 10.1016/j.celrep.2021.109807},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/332056,

title = {Factor-Based Framework for Multivariate and Multi-step-ahead Forecasting of Large Scale Time Series},

author = {Jacopo De Stefani and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/332056},

year  = {2021},

date = {2021-01-01},

journal = {Frontiers in Big Data},

volume = {4},

note = {DOI: 10.3389/fdata.2021.690267},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/331622,

title = {Transfer Learning Strategies for Credit Card Fraud Detection},

author = {Bertrand Lebichot and Theo Verhelst and Yann-A"el Le Borgne and Liyun He-Guelton and Frédéric Oblé and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/331622},

year  = {2021},

date = {2021-01-01},

journal = {IEEE access},

volume = {9},

pages = {114754-114766},

note = {DOI: 10.1109/ACCESS.2021.3104472},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/333678,

title = {DNAModAnnot: A R toolbox for DNA modification filtering and annotation},

author = {Alexis Hardy and Mélody Matelot and Amandine Touzeau and Christophe Klopp and Céline Lopez-Roques and Sandra Duharcourt and Matthieu Defrance},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/333678},

year  = {2021},

date = {2021-01-01},

journal = {Bioinformatics},

volume = {37},

number = {17},

pages = {2738-2740},

note = {DOI: 10.1093/bioinformatics/btab032},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/331774,

title = {Incremental learning strategies for credit cards fraud detection},

author = {Bertrand Lebichot and Gian Marco Paldino and Wissam Siblini and Liyun He-Guelton and Frédéric Oblé and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/331774},

year  = {2021},

date = {2021-01-01},

journal = {International journal of data science and analytics (Print)},

volume = {12},

number = {2},

pages = {165-174},

note = {DOI: 10.1007/s41060-021-00258-0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/331459,

title = {A Modern Reconstruction of Richard Carrington’s Observations (1853–1861)},

author = {S. Bhattacharya and E. T. H. Teague and Susanne Fay and Laure Lef`evre and Maarten Jansen and Frédéric L. Clette},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/331459},

year  = {2021},

date = {2021-01-01},

journal = {Solar physics},

volume = {296},

number = {8},

note = {DOI: 10.1007/s11207-021-01864-8},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/321123b,

title = {The CLAIRE COVID-19 initiative: approach, experiences and recommendations},

author = {Gianluca Bontempi and Ricardo Chavarriaga and Hans Canck and Emanuela Girardi and Holger H. Hoos and Iarla Kilbane-Dawe and Tonio Ball and Ann Nowe and Jose Sousa and Davide Bacciu and Marco Aldinucci and Manlio Domenico and Alessandro Saffiotti and Marco Maratea},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/321123},

year  = {2021},

date = {2021-01-01},

journal = {Ethics and information technology},

note = {DOI: 10.1007/s10676-020-09567-7},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/322517b,

title = {A tutorial on network-wide multi-horizon traffic forecasting with deep learning},

author = {Giovanni Buroni and Gianluca Bontempi and Karl Determe},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/322517},

year  = {2021},

date = {2021-01-01},

journal = {CEUR Workshop Proceedings},

volume = {2841},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/330754,

title = {Modeling behavioral experiments on uncertainty and cooperation with population-based reinforcement learning},

author = {Elias Fernández Domingos and Jelena Grujić and Juan Carlos Burguillo and Francisco C. Santos and Tom Lenaerts},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/330754},

year  = {2021},

date = {2021-01-01},

journal = {Simulation modelling practice and theory},

volume = {109},

note = {DOI: 10.1016/j.simpat.2021.102299},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/325214b,

title = {Contrastive self-supervised clustering of scRNA-seq data.},

author = {Madalina Ciortan and Matthieu Defrance},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/325214},

year  = {2021},

date = {2021-01-01},

journal = {BMC bioinformatics},

volume = {22},

number = {1},

pages = {280},

note = {DOI: 10.1186/s12859-021-04210-8},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/332290,

title = {Molecular adaptations to heat stress in the thermophilic ant genus Cataglyphis},

author = {Rémy Perez and Natalia Souza Araujo and Matthieu Defrance and Serge Aron},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/332290},

year  = {2021},

date = {2021-01-01},

journal = {Molecular ecology},

note = {DOI: 10.1111/mec.16134},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/322462b,

title = {Multistage feedback-driven compartmental dynamics of hematopoiesis},

author = {Nathaniel Vincent Mon P`ere and Tom Lenaerts and Jorge Manuel dos Santos J. M. d. S. Pacheco and David Dingli},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/322462},

year  = {2021},

date = {2021-01-01},

journal = {iScience},

volume = {24},

number = {4},

note = {DOI: 10.1016/j.isci.2021.102326},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/316657,

title = {NR5A1 c.991-1G > C splice-site variant causes familial 46,XY partial gonadal dysgenesis with incomplete penetrance},

author = {Maris Laan and Laura Kasak and Kęstutis Timinskas and Marina Grigorova and Česlovas Venclovas and Alexandre Renaux and Tom Lenaerts and Margus Punab},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/316657},

year  = {2021},

date = {2021-01-01},

journal = {Clinical endocrinology},

note = {DOI: 10.1111/cen.14381},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/321049b,

title = {Repeated interaction and its impact on cooperation and surplus allocation—an experimental analysis},

author = {Sibilla Di Guida and The Anh T. A. H. Han and Georg Kirchsteiger and Tom Lenaerts and Ioannis Zisis},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/321049},

year  = {2021},

date = {2021-01-01},

journal = {Games},

volume = {12},

number = {1},

note = {DOI: 10.3390/g12010025},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/320376,

title = {Mediating artificial intelligence developments through negative and positive incentives},

author = {The Anh T. A. H. Han and Luís Moniz Pereira and Tom Lenaerts and Francisco F. C. Santos},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/320376},

year  = {2021},

date = {2021-01-01},

journal = {PloS one},

volume = {16},

number = {1 January},

note = {DOI: 10.1371/journal.pone.0244592},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/322914,

title = {Mg deficiency interacts with the circadian clock and phytochromes pathways in Arabidopsis},

author = {Quentin Rivi{`e}re and Qiying Xiao and Annelie Gutsch and Matthieu Defrance and A A R Webb and Nathalie Verbruggen},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/322914/3/MgDeficiencyInPlantsLightClock.pdf},

year  = {2021},

date = {2021-01-01},

journal = {Annals of Applied Biology},

volume = {178},

number = {2},

pages = {387-399},

note = {DOI: 10.1111/aab.12659},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/326786,

title = {AST-MTL: An Attention-based Multi-Task Learning Strategy for Traffic Forecasting},

author = {Giovanni Buroni and Bertrand Lebichot and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/326786},

year  = {2021},

date = {2021-01-01},

journal = {IEEE access},

note = {DOI: 10.1109/ACCESS.2021.3083412},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/335292,

title = {Predicting Reach to Find Persuadable Customers: Improving Uplift Models for Churn Prevention},

author = {Theo Verhelst and Jeevan Shrestha and Denis Mercier and Jean Christophe Dewitte and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/335292},

year  = {2021},

date = {2021-01-01},

journal = {Lecture notes in computer science},

volume = {12986 LNAI},

pages = {44-54},

note = {DOI: 10.1007/978-3-030-88942-5_4},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/322462,

title = {Multistage feedback-driven compartmental dynamics of hematopoiesis},

author = {Nathaniel Vincent Mon P{`e}re and Tom Lenaerts and Jorge Manuel Santos J M d S dos Pacheco and David Dingli},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/322462/1/doi_306106.pdf},

year  = {2021},

date = {2021-01-01},

journal = {iScience},

volume = {24},

number = {4},

abstract = {Human hematopoiesis is surprisingly resilient to disruptions, providing suitable responses to severe bleeding, long-lasting immune activation, and even bone marrow transplants. Still, many blood disorders exist which push the system past its natural plasticity, resulting in abnormalities in the circulating blood. While proper treatment of such diseases can benefit from understanding the underlying cell dynamics, these are non-trivial to predict due to the hematopoietic system's hierarchical nature and complex feedback networks. To characterize the dynamics following different types of perturbations, we investigate a model representing hematopoiesis as a sequence of compartments covering all maturation stages---from stem to mature cells---where feedback regulates cell production to ongoing necessities. We find that a stable response to perturbations requires the simultaneous adaptation of cell differentiation and self-renewal rates, and show that under conditions of continuous disruption---as found in chronic hemolytic states---compartment cell numbers evolve to novel stable states.},

note = {DOI: 10.1016/j.isci.2021.102326},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/321049,

title = {Repeated interaction and its impact on cooperation and surplus allocation---an experimental analysis},

author = {Sibilla Di Guida and The Anh T A H Han and Georg Kirchsteiger and Tom Lenaerts and Ioannis Zisis},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/321049/1/doi_304693.pdf},

year  = {2021},

date = {2021-01-01},

journal = {Games},

volume = {12},

number = {1},

abstract = {This paper investigates how the possibility of affecting group composition combined with the possibility of repeated interaction impacts cooperation within groups and surplus distribution. We developed and tested experimentally a Surplus Allocation Game where cooperation of four agents is needed to produce surplus, but only two have the power to allocate it among the group members. Three matching procedures (corresponding to three separate experimental treatments) were used to test the impact of the variables of interest. A total of 400 subjects participated in our research, which was computer-based and conducted in a laboratory. Our results show that allowing for repeated interaction with the same partners leads to a self-selection of agents into groups with different life spans, whose duration is correlated with the behavior of both distributors and receivers. While behavior at the group level is diverse for surplus allocation and amount of cooperation, aggregate behavior is instead similar when repeated interaction is allowed or not allowed. We developed a behavioral model that captures the dynamics observed in the experimental data and sheds light into the rationales that drive the agents' individual behavior, suggesting that the most generous distributors are those acting for fear of rejection, not for true generosity, while the groups lasting the longest are those composed by this type of distributors and ``undemanding'' receivers.},

note = {DOI: 10.3390/g12010025},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/296188,

title = {Digenic inheritance of human primary microcephaly delineates centrosomal and non centrosomal pathways.},

author = {Sarah Duerinckx and Valérie Jacquemin and Séverine Drunat and Yoann Vial and Sandrine Passemard and Camille Perazzolo and Annick Massart and Julie Soblet and Judith Racapé and Laurence Desmyter and Cindy Badoer and Sofia Papadimitriou and Yann-A{"e}l Le Borgne and Anne Lefort and Frédérick Libert and Viviane De Maertelaer and Marianne Rooman and Sabine Costagliola and Alain Verloes and Tom Lenaerts and Isabelle Pirson and Marc Abramowicz},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/296188/4/Supp_Mat.pdf},

year  = {2020},

date = {2020-01-01},

journal = {Human mutation},

volume = {41},

number = {2},

pages = {512-524},

abstract = {Primary Microcephaly (PM) is characterized by a small head since birth and is vastly heterogeneous both genetically and phenotypically. While most cases are monogenic, genetic interactions between Aspm and Wdr62 have recently been described in a mouse model of PM. Here, we used two complementary, holistic in vivo approaches: high throughput DNA sequencing of multiple PM genes in human PM patients, and genome-edited zebrafish modeling for digenic inheritance of PM. Exomes of PM patients showed a significant burden of variants in 75 PM genes, that persisted after removing monogenic causes of PM (e.g., biallelic pathogenic variants in CEP152). This observation was replicated in an independent cohort of PM patients, where a PM gene panel showed in addition that the burden was carried by six centrosomal genes. Allelic frequencies were consistent with digenic inheritance. In zebrafish, non-centrosomal gene casc5 -/- produced a severe PM phenotype, that was not modified by centrosomal genes aspm or wdr62 invalidation. A digenic, quadriallelic PM phenotype was produced by aspm and wdr62. Our observations provide strong evidence for digenic inheritance of human PM, involving centrosomal genes. Absence of genetic interaction between casc5 and aspm or wdr62 further delineates centrosomal and non-centrosomal pathways in PM. This article is protected by copyright. All rights reserved.},

note = {DOI: 10.1002/humu.23948},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/301750,

title = {Interpreting pathways to discover cancer driver genes with Moonlight},

author = {Antonio Colaprico and Catharina Olsen and Matthew Bailey and Gabriel G J Odom and Thilde Terkelsen and Tiago Chedraoui Silva and André Vidas Olsen and Laura Cantini and Andrey Zinovyev and Emmanuel Barillot and Houtan Noushmehr and Gloria Bertoli and Isabella Castiglioni and Claudia Cava and Gianluca Bontempi and Xi Steven Chen and Elena Papaleo},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/301750/1/doi_285394.pdf},

year  = {2020},

date = {2020-01-01},

journal = {Nature communications},

volume = {11},

number = {1},

abstract = {Cancer driver gene alterations influence cancer development, occurring in oncogenes, tumor suppressors, and dual role genes. Discovering dual role cancer genes is difficult because of their elusive context-dependent behavior. We define oncogenic mediators as genes controlling biological processes. With them, we classify cancer driver genes, unveiling their roles in cancer mechanisms. To this end, we present Moonlight, a tool that incorporates multiple -omics data to identify critical cancer driver genes. With Moonlight, we analyze 8000+ tumor samples from 18 cancer types, discovering 3310 oncogenic mediators, 151 having dual roles. By incorporating additional data (amplification, mutation, DNA methylation, chromatin accessibility), we reveal 1000+ cancer driver genes, corroborating known molecular mechanisms. Additionally, we confirm critical cancer driver genes by analysing cell-line datasets. We discover inactivation of tumor suppressors in intron regions and that tissue type and subtype indicate dual role status. These findings help explain tumor heterogeneity and could guide therapeutic decisions.},

note = {DOI: 10.1038/s41467-019-13803-0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/317394,

title = {Hyperscanning EEG and Classification Based on Riemannian Geometry for Festive and Violent Mental State Discrimination},

author = {Cédric Simar and Ana Maria Cebolla and Ga{"e}lle Chartier and Mathieu Petieau and Gianluca Bontempi and Alain Berthoz and Guy Cheron},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/317394/3/pdf},

year  = {2020},

date = {2020-01-01},

journal = {Frontiers in Neuroscience},

volume = {14},

abstract = {Interactions between two brains constitute the essence of social communication. Daily movements are commonly executed during social interactions and are determined by different mental states that may express different positive or negative behavioral intent. In this context, the effective recognition of festive or violent intent before the action execution remains crucial for survival. Here, we hypothesize that the EEG signals contain the distinctive features characterizing movement intent already expressed before movement execution and that such distinctive information can be identified by state-of-the-art classification algorithms based on Riemannian geometry. We demonstrated for the first time that a classifier based on covariance matrices and Riemannian geometry can effectively discriminate between neutral, festive, and violent mental states only on the basis of non-invasive EEG signals in both the actor and observer participants. These results pave the way for new electrophysiological discrimination of mental states based on non-invasive EEG recordings and cutting-edge machine learning techniques.},

note = {DOI: 10.3389/fnins.2020.588357},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/314435,

title = {Robust Assessment of Short-Term Wind Power Forecasting Models on Multiple Time Horizons},

author = {Fabrizio De Caro and Jacopo De Stefani and Gianluca Bontempi and Alfredo A Vaccaro and Domenico D Villacci},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/314435/1/doi_298079.pdf},

year  = {2020},

date = {2020-01-01},

journal = {Technology and Economics of Smart Grids and Sustainable Energy},

volume = {5},

number = {1},

abstract = {The massive penetration of renewable power generation in modern power grids is an effective way to reduce the impact of energy production on global warming. Unfortunately, the wind power generation may affect the regular operation of electrical systems, due to the stochastic and intermittent nature of the wind. For this reason, reducing the uncertainty about the wind evolution, e.g. by using short-term wind power forecasting methodologies, is a priority for system operators and wind producers to implement low-carbon power grids. Unfortunately, though the complexity of this task implies the comparison of several alternative forecasting methodologies and dimensionality reduction techniques, a general and robust procedure of model assessment still lacks in literature. In this paper the authors propose a robust methodology, based on extensive statistical analysis and resampling routines, to supply the most effective wind power forecasting method by testing a vast ensemble of methodologies over multiple time-scales and on a real case study. Experimental results on real data collected in an Italian wind farm show the potential of ensemble approaches integrating both statistical and machine learning methods.},

note = {DOI: 10.1007/s40866-020-00090-8},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/305060,

title = {Retinal endothelial cell phenotypic modifications during experimental autoimmune uveitis: A transcriptomic approach},

author = {D Lipski and Vincent Foucart and Remi Dewispelaere and Laure Caspers and Matthieu Defrance and Catherine Bruyns and Francois Willermain},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/305060/1/doi_288704.pdf},

year  = {2020},

date = {2020-01-01},

journal = {BMC ophthalmology},

volume = {20},

number = {1},

abstract = {Background: Blood-retinal barrier cells are known to exhibit a massive phenotypic change during experimental autoimmune uveitis (EAU) development. In an attempt to investigate the mechanisms of blood-retinal barrier (BRB) breakdown at a global level, we studied the gene regulation of total retinal cells and retinal endothelial cells during non-infectious uveitis. Methods: Retinal endothelial cells were isolated by flow cytometry either in Tie2-GFP mice (CD31+ CD45- GFP+ cells), or in wild type C57BL/6 mice (CD31+ CD45- endoglin+ cells). EAU was induced in C57BL/6 mice by adoptive transfer of IRBP1-20-specific T cells. Total retinal cells and retinal endothelial cells from na"ive and EAU mice were sorted and their gene expression compared by RNA-Seq. Protein expression of selected genes was validated by immunofluorescence on retinal wholemounts and cryosections and by flow cytometry. Results: Retinal endothelial cell sorting in wild type C57BL/6 mice was validated by comparative transcriptome analysis with retinal endothelial cells sorted from Tie2-GFP mice, which express GFP under the control of the endothelial-specific receptor tyrosine kinase promoter Tie2. RNA-Seq analysis of total retinal cells mainly brought to light upregulation of genes involved in antigen presentation and T cell activation during EAU. Specific transcriptome analysis of retinal endothelial cells allowed us to identify 82 genes modulated in retinal endothelial cells during EAU development. Protein expression of 5 of those genes (serpina3n, lcn2, ackr1, lrg1 and lamc3) was validated at the level of inner BRB cells. Conclusion: Those data not only confirm the involvement of known pathogenic molecules but further provide a list of new candidate genes and pathways possibly implicated in inner BRB breakdown during non-infectious posterior uveitis.},

note = {DOI: 10.1186/s12886-020-1333-5},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/316017,

title = {Combining single-cell RNA-sequencing with a molecular atlas unveils new markers for Caenorhabditis elegans neuron classes},

author = {Ramiro Lorenzo and Michiho Onizuka and Matthieu Defrance and Patrick Laurent},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/316017/1/doi_299661.pdf},

year  = {2020},

date = {2020-01-01},

journal = {Nucleic acids research},

abstract = {Abstract Single-cell RNA-sequencing (scRNA-seq) of the Caenorhabditis elegans nervous system offers the unique opportunity to obtain a partial expression profile for each neuron within a known connectome. Building on recent scRNA-seq data and on a molecular atlas describing the expression pattern of ∼800 genes at the single cell resolution, we designed an iterative clustering analysis aiming to match each cell-cluster to the ∼100 anatomically defined neuron classes of C. elegans. This heuristic approach successfully assigned 97 of the 118 neuron classes to a cluster. Sixty two clusters were assigned to a single neuron class and 15 clusters grouped neuron classes sharing close molecular signatures. Pseudotime analysis revealed a maturation process occurring in some neurons (e.g. PDA) during the L2 stage. Based on the molecular profiles of all identified neurons, we predicted cell fate regulators and experimentally validated unc-86 for the normal differentiation of RMG neurons. Furthermore, we observed that different classes of genes functionally diversify sensory neurons, interneurons and motorneurons. Finally, we designed 15 new neuron class-specific promoters validated in vivo. Amongst them, 10 represent the only specific promoter reported to this day, expanding the list of neurons amenable to genetic manipulations.},

note = {DOI: 10.1093/nar/gkaa486},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/308993b,

title = {Dynamic contact networks of patients and MRSA spread in hospitals},

author = {Luis Mateus Rocha and Vikramjit Singh and Markus Esch and Tom Lenaerts and Fredrik Liljeros and Anna Thorson},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/308993},

year  = {2020},

date = {2020-01-01},

journal = {Scientific reports},

volume = {10},

number = {1},

note = {DOI: 10.1038/s41598-020-66270-9},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/315240b,

title = {Timing Uncertainty in Collective Risk Dilemmas Encourages Group Reciprocation and Polarization},

author = {Elias Fernández Domingos and Jelena Grujić and Juan J. C. Burguillo and Georg Kirchsteiger and Francisco C. Santos and Tom Lenaerts},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/315240},

year  = {2020},

date = {2020-01-01},

journal = {iScience},

volume = {23},

number = {12},

note = {DOI: 10.1016/j.isci.2020.101752},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/336088,

title = {From digenic combinations to oligogenic networks via a new predictive approach},

author = {Tom Lenaerts},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/336088},

year  = {2020},

date = {2020-01-01},

journal = {European journal of human genetics},

volume = {28},

number = {1},

note = {DOI: 10.1038/s41431-020-00740-6},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/301750b,

title = {Interpreting pathways to discover cancer driver genes with Moonlight},

author = {Antonio Colaprico and Catharina Olsen and Matthew Bailey and Gabriel G. J. Odom and Thilde Terkelsen and Tiago Chedraoui Silva and André Vidas Olsen and Laura Cantini and Andrey Zinovyev and Emmanuel Barillot and Houtan Noushmehr and Gloria Bertoli and Isabella Castiglioni and Claudia Cava and Gianluca Bontempi and Xi Steven Chen and Elena Papaleo},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/301750},

year  = {2020},

date = {2020-01-01},

journal = {Nature communications},

volume = {11},

number = {1},

note = {DOI: 10.1038/s41467-019-13803-0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/317394b,

title = {Hyperscanning EEG and Classification Based on Riemannian Geometry for Festive and Violent Mental State Discrimination},

author = {Cédric Simar and Ana Maria Cebolla and Ga"elle Chartier and Mathieu Petieau and Gianluca Bontempi and Alain Berthoz and Guy Cheron},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/317394},

year  = {2020},

date = {2020-01-01},

journal = {Frontiers in Neuroscience},

volume = {14},

note = {DOI: 10.3389/fnins.2020.588357},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/313950,

title = {Robust Assessment of Short-Term Wind Power Forecasting Models on Multiple Time Horizons},

author = {Fabrizio De Caro and Jacopo De Stefani and Gianluca Bontempi and Alfredo A. Vaccaro and Domenico D. Villacci},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/313950},

year  = {2020},

date = {2020-01-01},

journal = {Technology and Economics of Smart Grids and Sustainable Energy},

volume = {5},

number = {1},

note = {DOI: 10.1007/s40866-020-00090-8},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/322914b,

title = {Mg deficiency interacts with the circadian clock and phytochromes pathways in Arabidopsis},

author = {Quentin Rivi`ere and Qiying Xiao and Annelie Gutsch and Matthieu Defrance and A. A. R. Webb and Nathalie Verbruggen},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/322914},

year  = {2020},

date = {2020-01-01},

journal = {Annals of Applied Biology},

volume = {178},

number = {2},

pages = {387-399},

note = {DOI: 10.1111/aab.12659},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/314435b,

title = {Robust Assessment of Short-Term Wind Power Forecasting Models on Multiple Time Horizons},

author = {Fabrizio De Caro and Jacopo De Stefani and Gianluca Bontempi and Alfredo A. Vaccaro and Domenico D. Villacci},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/314435},

year  = {2020},

date = {2020-01-01},

journal = {Technology and Economics of Smart Grids and Sustainable Energy},

volume = {5},

number = {1},

note = {DOI: 10.1007/s40866-020-00090-8},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/316619,

title = {Density Estimation Using Multiscale Local Polynomial Transforms},

author = {Maarten Jansen},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/316619},

year  = {2020},

date = {2020-01-01},

journal = {Springer Proceedings in Mathematics and Statistics},

volume = {339},

pages = {249-260},

note = {DOI: 10.1007/978-3-030-57306-5_23},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/316645,

title = {Correction for Optimisation Bias in Structured Sparse High-Dimensional Variable Selection},

author = {Bastien Marquis and Maarten Jansen},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/316645},

year  = {2020},

date = {2020-01-01},

journal = {Springer Proceedings in Mathematics and Statistics},

volume = {339},

pages = {357-365},

note = {DOI: 10.1007/978-3-030-57306-5_32},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/312667b,

title = {Infiltrative tumour growth pattern correlates with poor outcome in oesophageal cancer.},

author = {Ma"elle Anciaux and Pieter Demetter and Roland De Wind and Maria Gomez Galdon and Sylvie Vande Velde and Gaspard Lens and Ligia Ioana Ruscas-Craciun and Amélie Deleruelle and Denis Larsimont and Tom Lenaerts and Francesco Sclafani and Amélie Deleporte and Vincent Donckier and Alain Hendlisz and Caroline Vandeputte},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/312667},

year  = {2020},

date = {2020-01-01},

journal = {BMJ open gastroenterology},

volume = {7},

number = {1},

note = {DOI: 10.1136/bmjgast-2020-000431},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/313051b,

title = {Do people imitate when making decisions? Evidence from a spatial Prisoner's Dilemma experiment: Do people imitate when making decisions},

author = {Jelena Grujić and Tom Lenaerts},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/313051},

year  = {2020},

date = {2020-01-01},

journal = {Royal Society open science},

volume = {7},

number = {7},

note = {DOI: 10.1098/rsos.200618},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/312458,

title = {Circulating unmethylated CHTOP and INS DNA fragments provide evidence of possible islet cell death in youth with obesity and diabetes},

author = {Farooq Syed and Sarah SA Tersey and Jean Valéry Turatsinze and Jamie J. L. Felton and Nicole Jiyun Kang and Jennifer J. B. Nelson and Emily EK Sims and Matthieu Defrance and Martin Bizet and Franccois Fuks and Miriam Cnop and Marco Bugliani and Piero Marchetti and Anette Gabriele Ziegler and Ezio Bonifacio and Bobbie Jo B. J. M. Webb-Robertson and Appakalai A. N. Balamurugan and Carmella Evans-Molina and Decio L. Eizirik and Kieren K. J. Mather and Silva Arslanian and Raghavendra R. G. Mirmira},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/312458},

year  = {2020},

date = {2020-01-01},

journal = {Clinical Epigenetics},

volume = {12},

number = {1},

pages = {116},

note = {DOI: 10.1186/s13148-020-00906-5},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/316017b,

title = {Combining single-cell RNA-sequencing with a molecular atlas unveils new markers for Caenorhabditis elegans neuron classes},

author = {Ramiro Lorenzo and Michiho Onizuka and Matthieu Defrance and Patrick Laurent},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/316017},

year  = {2020},

date = {2020-01-01},

journal = {Nucleic acids research},

note = {DOI: 10.1093/nar/gkaa486},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/319033b,

title = {To regulate or not: A social dynamics analysis of an idealised ai race},

author = {The Anh T. A. H. Han and Luís Marcelo Pereira and Francisco C. Santos and Tom Lenaerts},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/319033},

year  = {2020},

date = {2020-01-01},

journal = {The journal of artificial intelligence research},

volume = {69},

pages = {881-921},

note = {DOI: 10.1613/JAIR.1.12225},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/305060b,

title = {Retinal endothelial cell phenotypic modifications during experimental autoimmune uveitis: A transcriptomic approach},

author = {Deborah Lipski and Vincent Foucart and Remi Dewispelaere and Laure Caspers and Matthieu Defrance and Catherine Bruyns and Francois Willermain},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/305060},

year  = {2020},

date = {2020-01-01},

journal = {BMC ophthalmology},

volume = {20},

number = {1},

note = {DOI: 10.1186/s12886-020-1333-5},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/296188b,

title = {Digenic inheritance of human primary microcephaly delineates centrosomal and non centrosomal pathways.},

author = {Sarah Duerinckx and Valérie Jacquemin and Séverine Drunat and Yoann Vial and Sandrine Passemard and Camille Perazzolo and Annick Massart and Julie Soblet and Judith Racapé and Laurence Desmyter and Cindy Badoer and Sofia Papadimitriou and Yann-A"el Le Borgne and Anne Lefort and Frédérick Libert and Viviane De Maertelaer and Marianne Rooman and Sabine Costagliola and Alain Verloes and Tom Lenaerts and Isabelle Pirson and Marc Abramowicz},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/296188},

year  = {2020},

date = {2020-01-01},

journal = {Human mutation},

volume = {41},

number = {2},

pages = {512-524},

note = {DOI: 10.1002/humu.23948},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/319033,

title = {To regulate or not: A social dynamics analysis of an idealised ai race},

author = {The Anh T A H Han and Lu{'i}s Marcelo Pereira and Francisco C Santos and Tom Lenaerts},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/319033/17/1907-12393.pdf},

year  = {2020},

date = {2020-01-01},

journal = {The journal of artificial intelligence research},

volume = {69},

pages = {881-921},

abstract = {Rapid technological advancements in Artificial Intelligence (AI), as well as the growing deployment of intelligent technologies in new application domains, have generated serious anxiety and a fear of missing out among different stake-holders, fostering a racing narrative. Whether real or not, the belief in such a race for domain supremacy through AI, can make it real simply from its consequences, as put forward by the Thomas theorem. These consequences may be negative, as racing for technological supremacy creates a complex ecology of choices that could push stake-holders to underestimate or even ignore ethical and safety procedures. As a consequence, different actors are urging to consider both the normative and social impact of these technological advancements, contemplating the use of the precautionary principle in AI innovation and research. Yet, given the breadth and depth of AI and its advances, it is difficult to assess which technology needs regulation and when. As there is no easy access to data describing this alleged AI race, theoretical models are necessary to understand its potential dynamics, allowing for the identification of when procedures need to be put in place to favour outcomes beneficial for all. We show that, next to the risks of setbacks and being reprimanded for unsafe behaviour, the time-scale in which domain supremacy can be achieved plays a crucial role. When this can be achieved in a short term, those who completely ignore the safety precautions are bound to win the race but at a cost to society, apparently requiring regulatory actions. Our analysis reveals that imposing regulations for all risk and timing conditions may not have the anticipated effect as only for specific conditions a dilemma arises between what is individually preferred and globally beneficial. Similar observations can be made for the long-term development case. Yet different from the short-term situation, conditions can be identified that require the promotion of risk-taking as opposed to compliance with safety regulations in order to improve social welfare. These results remain robust both when two or several actors are involved in the race and when collective rather than individual setbacks are produced by risk-taking behaviour. When defining codes of conduct and regulatory policies for applications of AI, a clear understanding of the time-scale of the race is thus required, as this may induce important non-trivial effects.},

note = {DOI: 10.1613/JAIR.1.12225},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/316605,

title = {Collective Decision-Making as a Contextual Multi-armed Bandit Problem},

author = {Axel Abels and Tom Lenaerts and Vito Trianni and Ann Nowe},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/316605/5/colascdm.pdf},

year  = {2020},

date = {2020-01-01},

journal = {Lecture notes in computer science},

volume = {12496 LNAI},

pages = {113-124},

abstract = {Collective decision-making (CDM) processes -- wherein the knowledge of a group of individuals with a common goal must be combined to make optimal decisions -- can be formalized within the framework of the deciding with expert advice setting. Traditional approaches to tackle this problem focus on finding appropriate weights for the individuals in the group. In contrast, we propose here meta-CMAB, a meta approach that learns a mapping from expert advice to expected outcomes. In summary, our work reveals that, when trying to make the best choice in a problem with multiple alternatives, meta-CMAB assures that the collective knowledge of experts leads to the best outcome without the need for accurate confidence estimates.},

note = {DOI: 10.1007/978-3-030-63007-2_9},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/316598,

title = {How Expert Confidence Can Improve Collective Decision-Making in Contextual Multi-Armed Bandit Problems},

author = {Axel Abels and Tom Lenaerts and Vito Trianni and Ann Nowe},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/316598/4/howexpertconfidence.pdf},

year  = {2020},

date = {2020-01-01},

journal = {Lecture notes in computer science},

volume = {12496 LNAI},

pages = {125-138},

abstract = {In collective decision-making (CDM) a group of experts with a shared set of values and a common goal must combine their knowledge to make a collectively optimal decision. Whereas existing research on CDM primarily focuses on making binary decisions, we focus here on CDM applied to solving contextual multi-armed bandit (CMAB) problems, where the goal is to exploit contextual information to select the best arm among a set. To address the limiting assumptions of prior work, we introduce confidence estimates and propose a novel approach to deciding with expert advice which can take advantage of these estimates. We further show that, when confidence estimates are imperfect, the proposed approach is more robust than the classical confidence-weighted majority vote.},

note = {DOI: 10.1007/978-3-030-63007-2_10},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/315240,

title = {Timing Uncertainty in Collective Risk Dilemmas Encourages Group Reciprocation and Polarization},

author = {Elias Fernández Domingos and Jelena Gruji{'c} and Juan J C Burguillo and Georg Kirchsteiger and Francisco C Santos and Tom Lenaerts},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/315240/1/doi_298884.pdf},

year  = {2020},

date = {2020-01-01},

journal = {iScience},

volume = {23},

number = {12},

abstract = {Social dilemmas are often shaped by actions involving uncertain returns only achievable in the future, such as climate action or voluntary vaccination. In this context, uncertainty may produce non-trivial effects. Here, we assess experimentally --- through a collective risk dilemma --- the effect of timing uncertainty, i.e. how uncertainty about when a target needs to be reached affects the participants' behaviors. We show that timing uncertainty prompts not only early generosity but also polarized outcomes, where participants' total contributions are distributed unevenly. Furthermore, analyzing participants' behavior under timing uncertainty reveals an increase in reciprocal strategies. A data-driven game-theoretical model captures the self-organizing dynamics underpinning these behavioral patterns. Timing uncertainty thus casts a shadow on the future that leads participants to respond early, whereas reciprocal strategies appear to be important for group success. Yet, the same uncertainty also leads to inequity and polarization, requiring the inclusion of new incentives handling these societal issues.},

note = {DOI: 10.1016/j.isci.2020.101752},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/313051,

title = {Do people imitate when making decisions? Evidence from a spatial Prisoner's Dilemma experiment: Do people imitate when making decisions},

author = {Jelena Gruji{'c} and Tom Lenaerts},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/313051/3/rsos.200618.pdf},

year  = {2020},

date = {2020-01-01},

journal = {Royal Society open science},

volume = {7},

number = {7},

abstract = {How do people decide which action to take? This question is best answered using Game Theory, which has proposed a series of decision-making mechanisms that people potentially use. In network simulations, wherein games are repeated and pay-off differences can be observed, those mechanisms often rely on imitation of successful behaviour. Surprisingly, little to no evidence has been provided about whether people actually imitate more successful opponents when altering their actions in that context. By comparing two experimental treatments wherein participants play the iterated Prisoner's Dilemma game in a lattice, we aim to answer whether more successful actions are imitated. While in the first treatment, participants have the possibility to use pay-off differences in making their decision, the second treatment hinders such imitation as no information about the gains is provided. If imitation of the more successful plays a role then there should be a difference in how players switch from cooperation to defection between both treatments. Although, cooperation and pay-off levels do not appear to be significantly different between both treatments, detailed analysis shows that there are behavioural differences: when confronted with a more successful co-player, the focal player will imitate her behaviour as the switching is related to the experienced pay-off inequality.},

note = {DOI: 10.1098/rsos.200618},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/312667,

title = {Infiltrative tumour growth pattern correlates with poor outcome in oesophageal cancer.},

author = {Ma{"e}lle Anciaux and Pieter Demetter and Roland De Wind and Maria Gomez Galdon and Sylvie Vande Velde and Gaspard Lens and Ligia Craciun and Amélie Deleruelle and Denis Larsimont and Tom Lenaerts and Francesco Sclafani and Amélie Deleporte and Vincent Donckier and Alain Hendlisz and Caroline Vandeputte},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/312667/1/doi_296311.pdf},

year  = {2020},

date = {2020-01-01},

journal = {BMJ open gastroenterology},

volume = {7},

number = {1},

abstract = {Oesophageal cancer (OEC) is an aggressive disease with a poor survival rate. Prognostic markers are thus urgently needed. Due to the demonstrated prognostic value of histopathological growth pattern (HGP) in other cancers, we performed a retrospective assessment of HGP in patients suffering from invasive OEC.},

note = {DOI: 10.1136/bmjgast-2020-000431},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/308993,

title = {Dynamic contact networks of patients and MRSA spread in hospitals},

author = {Luis Mateus Rocha and Vikramjit Singh and Markus Esch and Tom Lenaerts and Fredrik Liljeros and Anna Thorson},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/308993/1/doi_292637.pdf},

year  = {2020},

date = {2020-01-01},

journal = {Scientific reports},

volume = {10},

number = {1},

abstract = {Methicillin-resistant Staphylococcus aureus (MRSA) is a difficult-to-treat infection. Increasing efforts have been taken to mitigate the epidemics and to avoid potential outbreaks in low endemic settings. Understanding the population dynamics of MRSA is essential to identify the causal mechanisms driving the epidemics and to generalise conclusions to different contexts. Previous studies neglected the temporal structure of contacts between patients and assumed homogeneous behaviour. We developed a high-resolution data-driven contact network model of interactions between 743,182 patients in 485 hospitals during 3,059 days to reproduce the exact contact sequences of the hospital population. Our model captures the exact spatial and temporal human contact behaviour and the dynamics of referrals within and between wards and hospitals at a large scale, revealing highly heterogeneous contact and mobility patterns of individual patients. A simulation exercise of epidemic spread shows that heterogeneous contacts cause the emergence of super-spreader patients, slower than exponential polynomial growth of the prevalence, and fast epidemic spread between wards and hospitals. In our simulated scenarios, screening upon hospital admittance is potentially more effective than reducing infection probability to reduce the final outbreak size. Our findings are useful to understand not only MRSA spread but also other hospital-acquired infections.},

note = {DOI: 10.1038/s41598-020-66270-9},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/296964,

title = {Towards a phylogenetic measure to quantify HIV incidence},

author = {Pieter Libin and Nassim Versbraegen and Ana A B Abecasis and Perpétua Gomes and Tom Lenaerts and Ann Nowe},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/296964/3/tapm.pdf},

year  = {2019},

date = {2019-01-01},

journal = {CEUR Workshop Proceedings},

volume = {2491},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/292462,

title = {Using game theory and decision decomposition to effectively discern and characterise bi-locus diseases},

author = {Nassim Versbraegen and Aziz Fouché and Charlotte Nachtegael and Sofia Papadimitriou and Andrea Gazzo and Guillaume Smits and Tom Lenaerts},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/292462/5/Elsevier_276089.pdf},

year  = {2019},

date = {2019-01-01},

journal = {Artificial intelligence in medicine},

volume = {99},

abstract = {In order to gain insight into oligogenic disorders, understanding those involving bi-locus variant combinations appears to be key. In prior work, we showed that features at multiple biological scales can already be used to discriminate among two types, i.e. disorders involving true digenic and modifier combinations. The current study expands this machine learning work towards dual molecular diagnosis cases, providing a classifier able to effectively distinguish between these three types. To reach this goal and gain an in-depth understanding of the decision process, game theory and tree decomposition techniques are applied to random forest predictors to investigate the relevance of feature combinations in the prediction. A machine learning model with high discrimination capabilities was developed, effectively differentiating the three classes in a biologically meaningful manner. Combining prediction interpretation and statistical analysis, we propose a biologically meaningful characterization of each class relying on specific feature strengths. Figuring out how biological characteristics shift samples towards one of three classes provides clinically relevant insight into the underlying biological processes as well as the disease itself.},

note = {DOI: 10.1016/j.artmed.2019.06.006},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/289958,

title = {ORVAL: a novel platform for the prediction and exploration of disease-causing oligogenic variant combinations.},

author = {Alexandre Renaux and Sofia Papadimitriou and Nassim Versbraegen and Charlotte Nachtegael and Simon Boutry and Ann Nowé and Guillaume Smits and Tom Lenaerts},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/289958/4/doi_273585.pdf},

year  = {2019},

date = {2019-01-01},

journal = {Nucleic acids research},

volume = {47},

number = {W1},

pages = {W93-W98},

abstract = {A tremendous amount of DNA sequencing data is being produced around the world with the ambition to capture in more detail the mechanisms underlying human diseases. While numerous bioinformatics tools exist that allow the discovery of causal variants in Mendelian diseases, little to no support is provided to do the same for variant combinations, an essential task for the discovery of the causes of oligogenic diseases. ORVAL (the Oligogenic Resource for Variant AnaLysis), which is presented here, provides an answer to this problem by focusing on generating networks of candidate pathogenic variant combinations in gene pairs, as opposed to isolated variants in unique genes. This online platform integrates innovative machine learning methods for combinatorial variant pathogenicity prediction with visualization techniques, offering several interactive and exploratory tools, such as pathogenic gene and protein interaction networks, a ranking of pathogenic gene pairs, as well as visual mappings of the cellular location and pathway information. ORVAL is the first web-based exploration platform dedicated to identifying networks of candidate pathogenic variant combinations with the sole ambition to help in uncovering oligogenic causes for patients that cannot rely on the classical disease analysis tools. ORVAL is available at https://orval.ibsquare.be.},

note = {DOI: 10.1093/nar/gkz437},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/289724,

title = {Predicting disease-causing variant combinations},

author = {Sofia Papadimitriou and Andrea Gazzo and Nassim Versbraegen and Charlotte Nachtegael and Jan Aerts and Yves Moreau and Sonia Van Dooren and Ann Nowe and Guillaume Smits and Tom Lenaerts},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/289724/4/doi_273351.pdf},

year  = {2019},

date = {2019-01-01},

journal = {Proceedings of the National Academy of Sciences of the United States of America},

volume = {116},

number = {24},

pages = {11878-11887},

abstract = {Notwithstanding important advances in the context of single-variant pathogenicity identification, novel breakthroughs in discerning the origins of many rare diseases require methods able to identify more complex genetic models. We present here the Variant Combinations Pathogenicity Predictor (VarCoPP), a machine-learning approach that identifies pathogenic variant combinations in gene pairs (called digenic or bilocus variant combinations). We show that the results produced by this method are highly accurate and precise, an efficacy that is endorsed when validating the method on recently published independent disease-causing data. Confidence labels of 95% and 99% are identified, representing the probability of a bilocus combination being a true pathogenic result, providing geneticists with rational markers to evaluate the most relevant pathogenic combinations and limit the search space and time. Finally, the VarCoPP has been designed to act as an interpretable method that can provide explanations on why a bilocus combination is predicted as pathogenic and which biological information is important for that prediction. This work provides an important step toward the genetic understanding of rare diseases, paving the way to clinical knowledge and improved patient care.},

note = {DOI: 10.1073/pnas.1815601116},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/303320,

title = {The Induction Problem: A Machine Learning Vindication Argument},

author = {Gianluca Bontempi},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/303320/3/lod2.pdf},

year  = {2019},

date = {2019-01-01},

journal = {Lecture notes in computer science},

volume = {11943 LNCS},

pages = {232-243},

abstract = {The problem of induction is a central problem in philosophy of science and concerns whether it is sound or not to extract laws from observational data. Nowadays, this issue is more relevant than ever given the pervasive and growing role of the data discovery process in all sciences. If on one hand induction is routinely employed by automatic machine learning techniques, on the other most of the philosophical work criticises induction as if an alternative could exist. But is there indeed a reliable alternative to induction? Is it possible to discover or predict something in a non inductive manner? This paper formalises the question on the basis of statistical notions (bias, variance, mean squared error) borrowed from estimation theory and statistical machine learning. The result is a justification of induction as rational behaviour. In a decision-making process a behaviour is rational if it is based on making choices that result in the most optimal level of benefit or utility. If we measure utility in a prediction context in terms of expected accuracy, it follows that induction is the rational way of conduct.},

note = {DOI: 10.1007/978-3-030-37599-7_20},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/289125,

title = {Combining unsupervised and supervised learning in credit card fraud detection},

author = {Fabrizio Carcillo and Yann-A{"e}l Le Borgne and Olivier Caelen and Yacine Kessaci and Frédéric Oblé and Gianluca Bontempi},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/289125/1/Elsevier_272752.pdf},

year  = {2019},

date = {2019-01-01},

journal = {Information sciences},

abstract = {Supervised learning techniques are widely employed in credit card fraud detection, as they make use of the assumption that fraudulent patterns can be learned from an analysis of past transactions. The task becomes challenging, however, when it has to take account of changes in customer behavior and fraudsters' ability to invent novel fraud patterns. In this context, unsupervised learning techniques can help the fraud detection systems to find anomalies. In this paper we present a hybrid technique that combines supervised and unsupervised techniques to improve the fraud detection accuracy. Unsupervised outlier scores, computed at different levels of granularity, are compared and tested on a real, annotated, credit card fraud detection dataset. Experimental results show that the combination is efficient and does indeed improve the accuracy of the detection.},

note = {DOI: 10.1016/j.ins.2019.05.042},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/292419,

title = {Comments on M4 competition},

author = {Gianluca Bontempi},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/292419/1/Elsevier_276046.pdf},

year  = {2019},

date = {2019-01-01},

journal = {International journal of forecasting},

note = {DOI: 10.1016/j.ijforecast.2019.03.028},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/286948,

title = {New functionalities in the TCGAbiolinks package for the study and integration of cancer data from GDC and GTEx},

author = {Mohamed Mounir and Marta Lucchetta and Tiago Henrique Da T C Silva and Catharina Olsen and Gianluca Bontempi and Xi Chen and Houtan Noushmehr and Antonio Colaprico and Elena Papaleo},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/286948},

year  = {2019},

date = {2019-01-01},

journal = {PLoS computational biology},

volume = {15},

number = {3},

pages = {e1006701},

abstract = {The advent of Next-Generation Sequencing (NGS) technologies has opened new perspectives in deciphering the genetic mechanisms underlying complex diseases. Nowadays, the amount of genomic data is massive and substantial efforts and new tools are required to unveil the information hidden in the data. The Genomic Data Commons (GDC) Data Portal is a platform that contains different genomic studies including the ones from The Cancer Genome Atlas (TCGA) and the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiatives, accounting for more than 40 tumor types originating from nearly 30000 patients. Such platforms, although very attractive, must make sure the stored data are easily accessible and adequately harmonized. Moreover, they have the primary focus on the data storage in a unique place, and they do not provide a comprehensive toolkit for analyses and interpretation of the data. To fulfill this urgent need, comprehensive but easily accessible computational methods for integrative analyses of genomic data that do not renounce a robust statistical and theoretical framework are required. In this context, the R/Bioconductor package TCGAbiolinks was developed, offering a variety of bioinformatics functionalities. Here we introduce new features and enhancements of TCGAbiolinks in terms of i) more accurate and flexible pipelines for differential expression analyses, ii) different methods for tumor purity estimation and filtering, iii) integration of normal samples from other platforms iv) support for other genomics datasets, exemplified here by the TARGET data. Evidence has shown that accounting for tumor purity is essential in the study of tumorigenesis, as these factors promote confounding behavior regarding differential expression analysis. With this in mind, we implemented these filtering procedures in TCGAbiolinks. Moreover, a limitation of some of the TCGA datasets is the unavailability or paucity of corresponding normal samples. We thus integrated into TCGAbiolinks the possibility to use normal samples from the Genotype-Tissue Expression (GTEx) project, which is another large-scale repository cataloging gene expression from healthy individuals. The new functionalities are available in the TCGAbiolinks version 2.8 and higher released in Bioconductor version 3.7.},

note = {DOI: 10.1371/journal.pcbi.1006701},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/296511,

title = {Understanding telecom customer churn with machine learning: From prediction to causal inference},

author = {Theo Verhelst and Olivier Caelen and Jean Christophe Dewitte and Bertrand Lebichot and Gianluca Bontempi},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/296511/3/abstract28.pdf},

year  = {2019},

date = {2019-01-01},

journal = {CEUR Workshop Proceedings},

volume = {2491},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/294385,

title = {EOMES interacts with RUNX3 and BRG1 to promote innate memory cell formation through epigenetic reprogramming},

author = {Nicolas Istaces and Marion Splittgerber and Viviana Lima Silva and Muriel Nguyen and Séverine Thomas and Aurore Le and Younes Achouri and Emilie Calonne and Matthieu Defrance and Fran{c c}ois Fuks and Stanislas Goriely and Abdulkader Azouz},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/294385/1/doi_278012.pdf},

year  = {2019},

date = {2019-01-01},

journal = {Nature communications},

volume = {10},

number = {1},

abstract = {Memory CD8+ T cells have the ability to provide lifelong immunity against pathogens. Although memory features generally arise after challenge with a foreign antigen, na"ive CD8 single positive (SP) thymocytes may acquire phenotypic and functional characteristics of memory cells in response to cytokines such as interleukin-4. This process is associated with the induction of the T-box transcription factor Eomesodermin (EOMES). However, the underlying molecular mechanisms remain ill-defined. Using epigenomic profiling, we show that these innate memory CD8SP cells acquire only a portion of the active enhancer repertoire of conventional memory cells. This reprograming is secondary to EOMES recruitment, mostly to RUNX3-bound enhancers. Furthermore, EOMES is found within chromatin-associated complexes containing BRG1 and promotes the recruitment of this chromatin remodelling factor. Also, the in vivo acquisition of EOMES-dependent program is BRG1-dependent. In conclusion, our results support a strong epigenetic basis for the EOMES-driven establishment of CD8+ T cell innate memory program.},

note = {DOI: 10.1038/s41467-019-11233-6},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/282177,

title = {Distinct mesoderm migration phenotypes in extra-embryonic and embryonic regions of the early mouse embryo},

author = {Bechara Saykali and Wallis Nahaboo and Navrita Mathiah and Marie-Lucie Racu and Matthieu Defrance and Isabelle Migeotte},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/282177/3/elife-42434-v1.pdf},

year  = {2019},

date = {2019-01-01},

journal = {eLife},

volume = {8},

abstract = {In mouse embryo gastrulation, epiblast cells delaminate at the primitive streak to form mesoderm and definitive endoderm, through an epithelial-mesenchymal transition. Mosaic expression of a membrane reporter in nascent mesoderm enabled recording cell shape and trajectory through live imaging. Upon leaving the streak, cells changed shape and extended protrusions of distinct size and abundance depending on the neighboring germ layer, as well as the region of the embryo. Embryonic trajectories were meandrous but directional, while extra-embryonic mesoderm cells showed little net displacement. Embryonic and extra-embryonic mesoderm transcriptomes highlighted distinct guidance, cytoskeleton, adhesion, and extracellular matrix signatures. Specifically, intermediate filaments were highly expressed in extra-embryonic mesoderm, while live imaging for F-actin showed abundance of actin filaments in embryonic mesoderm only. Accordingly, Rhoa or Rac1 conditional deletion in mesoderm inhibited embryonic, but not extra-embryonic mesoderm migration. Overall, this indicates separate cytoskeleton regulation coordinating the morphology and migration of mesoderm subpopulations.},

note = {DOI: 10.7554/eLife.42434.001},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/280731,

title = {Discussion on ``Model Confidence Bounds for Variable Selection'' by Yang Li, Yuetian Luo, Davide Ferrari, Xiaonan Hu, and Yichen Qin},

author = {G. Claeskens and Maarten Jansen},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/280731},

year  = {2019},

date = {2019-01-01},

journal = {Biometrics},

volume = {75},

number = {2},

pages = {404-406},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/287247,

title = {Discussion on “Model Confidence Bounds for Variable Selection” by Yang Li, Yuetian Luo, Davide Ferrari, Xiaonan Hu, and Yichen Qin},

author = {G. Claeskens and Maarten Jansen},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/287247},

year  = {2019},

date = {2019-01-01},

journal = {Biometrics},

note = {DOI: 10.1111/biom.13022},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/294385b,

title = {EOMES interacts with RUNX3 and BRG1 to promote innate memory cell formation through epigenetic reprogramming},

author = {Nicolas Istaces and Marion Splittgerber and Viviana Lima Silva and Muriel Nguyen and Séverine Thomas and Aurore Le and Younes Achouri and Emilie Calonne and Matthieu Defrance and Franccois Fuks and Stanislas Goriely and Abdulkader Azouz},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/294385},

year  = {2019},

date = {2019-01-01},

journal = {Nature communications},

volume = {10},

number = {1},

note = {DOI: 10.1038/s41467-019-11233-6},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/292462b,

title = {Using game theory and decision decomposition to effectively discern and characterise bi-locus diseases},

author = {Nassim Versbraegen and Aziz Fouché and Charlotte Nachtegael and Sofia Papadimitriou and Andrea Gazzo and Guillaume Smits and Tom Lenaerts},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/292462},

year  = {2019},

date = {2019-01-01},

journal = {Artificial intelligence in medicine},

volume = {99},

note = {DOI: 10.1016/j.artmed.2019.06.006},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/289958b,

title = {ORVAL: a novel platform for the prediction and exploration of disease-causing oligogenic variant combinations.},

author = {Alexandre Renaux and Sofia Papadimitriou and Nassim Versbraegen and Charlotte Nachtegael and Simon Boutry and Ann Nowé and Guillaume Smits and Tom Lenaerts},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/289958},

year  = {2019},

date = {2019-01-01},

journal = {Nucleic acids research},

volume = {47},

number = {W1},

pages = {W93-W98},

note = {DOI: 10.1093/nar/gkz437},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/289724b,

title = {Predicting disease-causing variant combinations},

author = {Sofia Papadimitriou and Andrea Gazzo and Nassim Versbraegen and Charlotte Nachtegael and Jan Aerts and Yves Moreau and Sonia Van Dooren and Ann Nowe and Guillaume Smits and Tom Lenaerts},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/289724},

year  = {2019},

date = {2019-01-01},

journal = {Proceedings of the National Academy of Sciences of the United States of America},

volume = {116},

number = {24},

pages = {11878-11887},

note = {DOI: 10.1073/pnas.1815601116},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/303320b,

title = {The Induction Problem: A Machine Learning Vindication Argument},

author = {Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/303320},

year  = {2019},

date = {2019-01-01},

journal = {Lecture notes in computer science},

volume = {11943 LNCS},

pages = {232-243},

note = {DOI: 10.1007/978-3-030-37599-7_20},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/289125b,

title = {Combining unsupervised and supervised learning in credit card fraud detection},

author = {Fabrizio Carcillo and Yann-A"el Le Borgne and Olivier Caelen and Yacine Kessaci and Frédéric Oblé and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/289125},

year  = {2019},

date = {2019-01-01},

journal = {Information sciences},

note = {DOI: 10.1016/j.ins.2019.05.042},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/292419b,

title = {Comments on M4 competition},

author = {Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/292419},

year  = {2019},

date = {2019-01-01},

journal = {International journal of forecasting},

note = {DOI: 10.1016/j.ijforecast.2019.03.028},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/282177b,

title = {Distinct mesoderm migration phenotypes in extra-embryonic and embryonic regions of the early mouse embryo},

author = {Bechara Saykali and Wallis Nahaboo and Navrita Mathiah and Marie-Lucie Racu and Matthieu Defrance and Isabelle Migeotte},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/282177},

year  = {2019},

date = {2019-01-01},

journal = {eLife},

volume = {8},

note = {DOI: 10.7554/eLife.42434.001},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/286948b,

title = {New functionalities in the TCGAbiolinks package for the study and integration of cancer data from GDC and GTEx},

author = {Mohamed Mounir and Marta Lucchetta and Tiago Henrique Da T. C. Silva and Catharina Olsen and Gianluca Bontempi and Xi Chen and Houtan Noushmehr and Antonio Colaprico and Elena Papaleo},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/286948},

year  = {2019},

date = {2019-01-01},

journal = {PLoS computational biology},

volume = {15},

number = {3},

pages = {e1006701},

note = {DOI: 10.1371/journal.pcbi.1006701},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/296964b,

title = {Towards a phylogenetic measure to quantify HIV incidence},

author = {Pieter Libin and Nassim Versbraegen and Ana A. B. Abecasis and Perpétua Gomes and Tom Lenaerts and Ann Nowe},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/296964},

year  = {2019},

date = {2019-01-01},

journal = {CEUR Workshop Proceedings},

volume = {2491},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/296511b,

title = {Understanding telecom customer churn with machine learning: From prediction to causal inference},

author = {Theo Verhelst and Olivier Caelen and Jean Christophe Dewitte and Bertrand Lebichot and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/296511},

year  = {2019},

date = {2019-01-01},

journal = {CEUR Workshop Proceedings},

volume = {2491},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/283645b,

title = {Large-scale in-silico statistical mutagenesis analysis sheds light on the deleteriousness landscape of the human proteome.},

author = {Daniele Raimondi and Gabriele Orlando and Francesco Tabaro and Tom Lenaerts and Marianne Rooman and Yves Moreau and Wim F Vranken},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/283645},

year  = {2018},

date = {2018-01-01},

journal = {Scientific reports},

volume = {8},

number = {1},

pages = {16980},

note = {DOI: 10.1038/s41598-018-34959-7},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/283230b,

title = {Batch and incremental dynamic factor machine learning for multivariate and multi-step-ahead forecasting},

author = {Jacopo De Stefani and Yann-A"el Le Borgne and Olivier Caelen and Dalila Hattab and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/283230},

year  = {2018},

date = {2018-01-01},

journal = {International journal of data science and analytics (Print)},

volume = {7},

number = {4},

pages = {311-329},

note = {DOI: 10.1007/s41060-018-0150-x},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/278063b,

title = {Comprehensive identification of long noncoding RNAs in colorectal cancer},

author = {Eric James Bony and Martin Bizet and Olivier Van Grembergen and Bouchra Hassabi and Emilie Calonne and Pascale Putmans and Gianluca Bontempi and Franccois Fuks},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/278063},

year  = {2018},

date = {2018-01-01},

journal = {Oncotarget},

volume = {9},

number = {45},

pages = {27605-27629},

note = {DOI: 10.18632/oncotarget.25218},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/311546b,

title = {Streaming active learning strategies for real-life credit card fraud detection: assessment and visualization},

author = {Fabrizio Carcillo and Yann-A"el Le Borgne and Olivier Caelen and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/311546},

year  = {2018},

date = {2018-01-01},

journal = {International journal of data science and analytics (Print)},

volume = {5},

number = {4},

pages = {285-300},

note = {DOI: 10.1007/s41060-018-0116-z},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/311389b,

title = {Correction to: Streaming active learning strategies for real-life credit detection: assessment and visualization},

author = {Fabrizio Carcillo and Yann-A"el Le Borgne and Olivier Caelen and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/311389},

year  = {2018},

date = {2018-01-01},

journal = {International journal of data science and analytics (Print)},

volume = {5},

number = {4},

pages = {301-302},

note = {DOI: 10.1007/s41060-018-0123-0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/272828b,

title = {Protect us from poor-quality medical research},

author = {J. P. A. Ioannidis and S. Bhattacharya and J. L. H. Evers and F. V. Der Veen and E. Somigliana and C. L. R. Barratt and Gianluca Bontempi and D. T. Baird and P. Crosignani and P Devroey and Klaus Diedrich and R. G. Farquharson and L. R. Fraser and Joep Pm M Geraedts and Luca Gianaroli and C. La Vecchia and C. Magli and E. Negri and A. Sunde and J. S. Tapanainen and Basil Tarlatzis and A. V. Steirteghem and A. Veiga},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/272828},

year  = {2018},

date = {2018-01-01},

journal = {Human reproduction},

volume = {33},

number = {5},

pages = {770-776},

note = {DOI: 10.1093/humrep/dey056},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/283645,

title = {Large-scale in-silico statistical mutagenesis analysis sheds light on the deleteriousness landscape of the human proteome.},

author = {Daniele Raimondi and Gabriele Orlando and Francesco Tabaro and Tom Lenaerts and Marianne Rooman and Yves Moreau and Wim F Vranken},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/283645/4/doi_267272.pdf},

year  = {2018},

date = {2018-01-01},

journal = {Scientific reports},

volume = {8},

number = {1},

pages = {16980},

abstract = {Next generation sequencing technologies are providing increasing amounts of sequencing data, paving the way for improvements in clinical genetics and precision medicine. The interpretation of the observed genomic variants in the light of their phenotypic effects is thus emerging as a crucial task to solve in order to advance our understanding of how exomic variants affect proteins and how the proteins' functional changes affect human health. Since the experimental evaluation of the effects of every observed variant is unfeasible, Bioinformatics methods are being developed to address this challenge in-silico, by predicting the impact of millions of variants, thus providing insight into the deleteriousness landscape of entire proteomes. Here we show the feasibility of this approach by using the recently developed DEOGEN2 variant-effect predictor to perform the largest in-silico mutagenesis scan to date. We computed the deleteriousness score of 170 million variants over 15000 human proteins and we analysed the results, investigating how the predicted deleteriousness landscape of the proteins relates to known functionally and structurally relevant protein regions and biophysical properties. Moreover, we qualitatively validated our results by comparing them with two mutagenesis studies targeting two specific proteins, showing the consistency of DEOGEN2 predictions with respect to experimental data.},

note = {DOI: 10.1038/s41598-018-34959-7},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/272556b,

title = {Flexible asynchronous simulation of iterated prisoner's dilemma based on actor model},

author = {Grażyna Skiba and Mateusz Starzec and Aleksander Byrski and Katarzyna Rycerz and Marek Kisiel-Dorohinicki and Wojciech Turek and Daniel Krzywicki and Tom Lenaerts and Juan Carlos Burguillo},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/272556},

year  = {2018},

date = {2018-01-01},

journal = {Simulation modelling practice and theory},

volume = {83},

pages = {75-92},

note = {DOI: 10.1016/j.simpat.2017.12.010},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/272556,

title = {Flexible asynchronous simulation of iterated prisoner's dilemma based on actor model},

author = {Gra{.z}yna Skiba and Mateusz Starzec and Aleksander Byrski and Katarzyna Rycerz and Marek Kisiel-Dorohinicki and Wojciech Turek and Daniel Krzywicki and Tom Lenaerts and Juan Carlos Burguillo},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/272556/1/Elsevier_256183.pdf},

year  = {2018},

date = {2018-01-01},

journal = {Simulation modelling practice and theory},

volume = {83},

pages = {75-92},

abstract = {The wide range of applications of the Iterated prisoner's dilemma (IPD) game made it a popular subject of study for the research community. As a consequence, numerous experiments have been conducted by researchers along the last decades. However, topics related with scaling simulation leveraging existing HPC infrastructure in the field of IPD did not always play a relevant role in such experimental work. The main contribution of this paper is a new simulation framework, based on asynchronous communication and its implementation oriented to distributed environments. Such framework is based on the modern Akka actor platform, that supports concurrent, distributed and resilient message-driven simulations; which are exemplified over the IPD game as a case study. We also present several interesting results regarding the introduction of asynchrony into the IPD simulation in order to obtain an efficient framework, so the whole simulation becomes scalable when using HPC facilities. The influence of asynchrony on the algorithm itself is also discussed, and the results show that it does not hamper the simulation.},

note = {DOI: 10.1016/j.simpat.2017.12.010},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/272541b,

title = {Chemical shift assignments of the partially deuterated Fyn SH2–SH3 domain},

author = {Fabien Kieken and Karine Loth and Nico N. A. J. Nuland and Peter Tompa and Tom Lenaerts},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/272541},

year  = {2018},

date = {2018-01-01},

journal = {Biomolecular N M R Assignments},

volume = {12},

number = {1},

pages = {117-122},

note = {DOI: 10.1007/s12104-017-9792-1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/272541,

title = {Chemical shift assignments of the partially deuterated Fyn SH2--SH3 domain},

author = {Fabien Kieken and Karine Loth and Nico N A J van Nuland and Peter Tompa and Tom Lenaerts},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/272541},

year  = {2018},

date = {2018-01-01},

journal = {Biomolecular N M R Assignments},

volume = {12},

number = {1},

pages = {117-122},

abstract = {Src Homology 2 and 3 (SH2 and SH3) are two key protein interaction modules involved in regulating the activity of many proteins such as tyrosine kinases and phosphatases by respective recognition of phosphotyrosine and proline-rich regions. In the Src family kinases, the inactive state of the protein is the direct result of the interaction of the SH2 and the SH3 domain with intra-molecular regions, leading to a closed structure incompetent with substrate modification. Here, we report the 1H, 15N and 13C backbone- and side-chain chemical shift assignments of the partially deuterated Fyn SH3--SH2 domain and structural differences between tandem and single domains. The BMRB accession number is 27165.},

note = {DOI: 10.1007/s12104-017-9792-1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/269084b,

title = {Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis},

author = {Eric Trepo and Nicolas Goossens and Naoto Fujiwara and Won-Min Song and Antonio Colaprico and Astrid Marot and Laurent Spahr and Pieter Demetter and Christine Sempoux and Gene Y Im and Joan Saldarriaga and Thierry Gustot and Jacques Devi`ere and Swan SN Thung and Charlotte Minsart and Thomas Serste and Gianluca Bontempi and Karim Abdelrahman and Jean Henrion and Delphine Degré and Valerio Lucidi and Laura Rubbia-Brandt and Venugopalan D Nair and Christophe Moreno and Pierre Deltenre and Yujin Hoshida and Denis Franchimont},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/269084},

year  = {2018},

date = {2018-01-01},

journal = {Gastroenterology},

volume = {154},

number = {4},

pages = {965-975},

note = {DOI: 10.1053/j.gastro.2017.10.048},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/270452b,

title = {In-silico integration approach to identify a key miRNA regulating a gene network in aggressive prostate cancer},

author = {Claudia Cava and Gloria Bertoli and Antonio Colaprico and Gianluca Bontempi and Giancarlo Mauri and Isabella Castiglioni},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/270452},

year  = {2018},

date = {2018-01-01},

journal = {International journal of molecular sciences},

volume = {19},

number = {3},

note = {DOI: 10.3390/ijms19030910},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/270586,

title = {Emergence of population structure in socio-cognitively inspired ant colony optimization},

author = {Aleksander Byrski and Ewelina {'S}widerska and Jakub {Ł}asisz and Marek Kisiel-Dorohinicki and Tom Lenaerts and Dana Samson and Bipin Indurkhya},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/270586/1/doi_254213.pdf},

year  = {2018},

date = {2018-01-01},

journal = {Computer Science},

volume = {19},

number = {1},

pages = {81-98},

abstract = {A metaheuristic proposed by us recently, Ant Colony Optimization (ACO) hybridized with socio-cognitive inspirations, turned out to generate interesting results when compared to classic ACO. Even though it does not always find better solutions to the considered problems, it usually finds sub-optimal solutions. Moreover, instead of a trial-and-error approach to configure the parameters of the ant species in the population, the actual structure of the population emerges from a predefined species-to-species ant migration strategies in our approach. Experimental results of our approach are compared to classic ACO and selected socio-cognitive versions of this algorithm.},

note = {DOI: 10.7494/csci.2018.19.1.2594},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/268207b,

title = {The transcription factors Runx3 and ThPOK cross-regulate acquisition of cytotoxic function by human Th1 lymphocytes.},

author = {Yasmina Serroukh and Chunyan Gu-Trantien and Baharak Hooshiar Kashani and Matthieu Defrance and Thien-Phong Vu Manh and Abdulkader Azouz and Aurélie Detavernier and Alice Hoyois and Jishnu Das and Martin Bizet and Emeline Pollet and Tressy Tabbuso and Emilie Calonne and Klaas Gisbergen and Marc Dalod and Franccois Fuks and Stanislas Goriely and Arnaud Marchant},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/268207},

year  = {2018},

date = {2018-01-01},

journal = {eLife},

volume = {7},

note = {DOI: 10.7554/eLife.30496},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/267360,

title = {Evolutionary Dynamics of Paroxysmal Nocturnal Hemoglobinuria},

author = {Nathaniel Mon P{`e}re and Tom Lenaerts and Jorge J M Pacheco and David Dingli},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/267360/4/doi_250987.pdf},

year  = {2018},

date = {2018-01-01},

journal = {PLoS computational biology},

volume = {14},

number = {6},

abstract = {Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal blood disorder characterized by hemolysis and a high risk of thrombosis, that is due to a deficiency in several cell surface proteins that prevent complement activation. Its origin has been traced to a somatic mutation in the PIG-A gene within hematopoietic stem cells (HSC). However, to date the question of how this mutant clone expands in size to contribute significantly to hematopoiesis remains under debate. One hypothesis posits the existence of a selective advantage of PIG-A mutated cells due to an immune mediated attack on normal HSC, but the evidence supporting this hypothesis is inconclusive. An alternative (and simpler) explanation attributes clonal expansion to neutral drift, in which case selection neither favours nor inhibits expansion of PIG-A mutated HSC. Here we examine the implications of the neutral drift model by numerically evolving a Markov chain for the probabilities of all possible outcomes, and investigate the possible occurrence and evolution, within this framework, of multiple independently arising clones within the HSC pool. Predictions of the model agree well with the known incidence of the disease and average age at diagnosis. Notwithstanding the slight difference in clonal expansion rates between our results and those reported in the literature, our model results lead to a relative stability of clone size when averaging multiple cases, in accord with what has been observed in human trials. The probability of a patient harbouring a second clone in the HSC pool was found to be extremely low (~10-8). Thus our results suggest that in clinical cases of PNH where two independent clones of mutant cells are observed, only one of those is likely to have originated in the HSC pool.},

note = {DOI: 10.1371/journal.pcbi.1006133},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/272529b,

title = {Changes in chromatin state reveal ARNT2 at a node of a tumorigenic transcription factor signature driving glioblastoma cell aggressiveness},

author = {Alexandra Bogeas and Ghislaine Morvan-Dubois and Elias E. A. El-Habr and Franccois Xavier Lejeune and Matthieu Defrance and Ashwin Narayanan and Klaudia Kuranda and Fanny Burel-Vandenbos and Salwa Sayd and Virgile Delaunay and Luiz Gustavo Feijó L. G. Dubois and Hugues Parrinello and Stéphanie Rialle and Sylvie Fabrega and Ahmed Idbaih and Jacques Haiech and Ivan Bieche and Thierry Virolle and Michele Goodhardt and Hervé Chneiweiss and Marie Pierre Junier},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/272529},

year  = {2018},

date = {2018-01-01},

journal = {Acta Neuropathologica},

volume = {135},

number = {2},

pages = {267-283},

note = {DOI: 10.1007/s00401-017-1783-x},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/267360b,

title = {Evolutionary Dynamics of Paroxysmal Nocturnal Hemoglobinuria},

author = {Nathaniel Mon P`ere and Tom Lenaerts and Jorge J. M. Pacheco and David Dingli},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/267360},

year  = {2018},

date = {2018-01-01},

journal = {PLoS computational biology},

volume = {14},

number = {6},

note = {DOI: 10.1371/journal.pcbi.1006133},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/270586b,

title = {Emergence of population structure in socio-cognitively inspired ant colony optimization},

author = {Aleksander Byrski and Ewelina Świderska and Jakub Łasisz and Marek Kisiel-Dorohinicki and Tom Lenaerts and Dana Samson and Bipin Indurkhya},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/270586},

year  = {2018},

date = {2018-01-01},

journal = {Computer Science},

volume = {19},

number = {1},

pages = {81-98},

note = {DOI: 10.7494/csci.2018.19.1.2594},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/282216b,

title = {Distinct mesoderm migration phenotypes in extra-embryonic and embryonic regions of the early mouse embryo},

author = {Bechara Saykali and Wallis Nahaboo and Navrita Mathiah and Marie-Lucie Racu and Matthieu Defrance and Isabelle Migeotte},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/282216},

year  = {2018},

date = {2018-01-01},

journal = {BioRxiv},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/269455b,

title = {Feature selection in high-dimensional dataset using MapReduce},

author = {Claudio Reggiani and Yann-A"el Le Borgne and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/269455},

year  = {2018},

date = {2018-01-01},

journal = {Communications in computer and information science},

volume = {823},

pages = {101-115},

note = {DOI: 10.1007/978-3-319-76892-2_8},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/268430b,

title = {Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis},

author = {Claudia Cava and Gloria Bertoli and Antonio Colaprico and Catharina Olsen and Gianluca Bontempi and Isabella Castiglioni},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/268430},

year  = {2018},

date = {2018-01-01},

journal = {BMC genomics},

volume = {19},

number = {1},

note = {DOI: 10.1186/s12864-017-4423-x},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/311579b,

title = {TCGAbiolinksGUI: A graphical user interface to analyze cancer molecular and clinical data [version 1; peer review: 1 approved, 1 approved with reservations]},

author = {Tiago Chedraoui Silva and Antonio Colaprico and Catharina Olsen and Tathiane Maistro Aistro T. M. Malta and Gianluca Bontempi and Michele Ceccarelli and Benjamin B. P. Berman and Houtan Noushmehr},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/311579},

year  = {2018},

date = {2018-01-01},

journal = {F1000Research},

volume = {7},

note = {DOI: 10.12688/F1000RESEARCH.14197.1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/272668b,

title = {Molecular chaperoning helps safeguarding mitochondrial integrity and motor functions in the Sahara silver ant Cataglyphis bombycina},

author = {Quentin Willot and Patrick Mardulyn and Matthieu Defrance and Cyril Gueydan and Serge Aron},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/272668},

year  = {2018},

date = {2018-01-01},

journal = {Scientific reports},

volume = {8},

note = {DOI: 10.1038/s41598-018-27628-2},

keywords = {},

pubstate = {published},

tppubtype = {article}

}