@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 = {https://dipot.ulb.ac.be/dspace/bitstream/2013/332056/1/doi_315700.pdf},

year  = {2021},

date = {2021-01-01},

journal = {Frontiers in Big Data},

volume = {4},

abstract = {State-of-the-art multivariate forecasting methods are restricted to low dimensional tasks, linear dependencies and short horizons. The technological advances (notably the Big data revolution) are instead shifting the focus to problems characterized by a large number of variables, non-linear dependencies and long forecasting horizons. In the last few years, the majority of the best performing techniques for multivariate forecasting have been based on deep-learning models. However, such models are characterized by high requirements in terms of data availability and computational resources and suffer from a lack of interpretability. To cope with the limitations of these methods, we propose an extension to the DFML framework, a hybrid forecasting technique inspired by the Dynamic Factor Model (DFM) approach, a successful forecasting methodology in econometrics. This extension improves the capabilities of the DFM approach, by implementing and assessing both linear and non-linear factor estimation techniques as well as model-driven and data-driven factor forecasting techniques. We assess several method integrations within the DFML, and we show that the proposed technique provides competitive results both in terms of forecasting accuracy and computational efficiency on multiple very large-scale (>10 2 variables and > 10 3 samples) real forecasting tasks.},

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

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 = {https://dipot.ulb.ac.be/dspace/bitstream/2013/331774/3/JDSA_2021_Article_.pdf},

year  = {2021},

date = {2021-01-01},

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

volume = {12},

number = {2},

pages = {165-174},

abstract = {Every second, thousands of credit or debit card transactions are processed in financial institutions. This extensive amount of data and its sequential nature make the problem of fraud detection particularly challenging. Most analytical strategies used in production are still based on batch learning, which is inadequate for two reasons: Models quickly become outdated and require sensitive data storage. The evolving nature of bank fraud enshrines the importance of having up-to-date models, and sensitive data retention makes companies vulnerable to infringements of the European General Data Protection Regulation. For these reasons, evaluating incremental learning strategies is recommended. This paper designs and evaluates incremental learning solutions for real-world fraud detection systems. The aim is to demonstrate the competitiveness of incremental learning over conventional batch approaches and, consequently, improve its accuracy employing ensemble learning, diversity and transfer learning. An experimental analysis is conducted on a full-scale case study including five months of e-commerce transactions and made available by our industry partner, Worldline.},

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

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:2013/326786,

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

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

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/326786/1/doi_310430.pdf},

year  = {2021},

date = {2021-01-01},

journal = {IEEE access},

abstract = {Road traffic forecasting is crucial in Intelligent Transportation Systems (ITS). To achieve accurate results, it is necessary to model the dynamic nature and the complex non-linear dependencies governing traffic. The goal is particularly challenging when the prediction involves more than just one traffic variable. This paper proposes a novel multi-task learning model, called AST-MTL, to perform multi-horizon predictions of the traffic flow and speed at the road network scale. The strategy combines a multilayer fully-connected neural network (FNN) and a multi-head attention mechanism to learn related tasks while improving generalization performance. The model also includes the graph convolutional network (GCNs) and the gated recurrent unit network (GRUs) to extract the spatial and temporal features of traffic conditions. Our experiments employ new sets of GPS data, called OBU data, to perform traffic prediction in the freeway and urban contexts. The experimental results prove our model can effectively perform multi-horizon traffic forecasting for different types of roads and outperform state-of-the-art models.},

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

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:2013/331459,

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

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

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/331459/3/Bhattacharya2021preprint.pdf},

year  = {2021},

date = {2021-01-01},

journal = {Solar physics},

volume = {296},

number = {8},

abstract = {The focus of this article is a re-count of Richard Carrington’s original sunspot observations from his book drawings (Carrington in Observations of the Spots on the Sun from November 9, 1853, to March 24, 1861 Made at Redhill, Williams and Norgate, London, 1863) by an observer from the World Data Center-SILSO (WDC-SILSO, http://www.sidc.be/silso/home) network, Thomas H. Teague (UK). This modern re-count will enable the recomputation of the entire Sunspot Number series in a way Carrington’s original counts (Casas and Vaquero in Solar Phys. 289(1), 79, 2014) did not. Here we present comparison studies of the new re-counted series with contemporary observations, new data extracted from the Journals of the Zürich Observatory and other sources of Carrington’s own observations and conclude that Carrington’s group counting is very close to the modern way of counting while his method for counting individual spots lags significantly behind modern counts. We also test the quality and robustness of the new recount with methods developed in Mathieu et al. (Astrophys. J. 886(1), 7, 2019).},

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

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:2013/305060c,

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 = {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 naïve 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:2013/367073,

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

author = {Elias Fernandez Domingos and Jelena Grujić and Juan Carlos Burguillo and Georg Kirchsteiger and Tom Lenaerts},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/367073/3/Timing.pdf},

year  = {2020},

date = {2020-01-01},

journal = {iScience},

volume = {23},

pages = {101752},

note = {Language of publication: fr},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/336088b,

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

author = {Tom Lenaerts},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/336088/1/doi_319732.pdf},

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:2013/308993c,

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:2013/313051c,

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 = {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:2013/319033c,

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 = {https://dipot.ulb.ac.be/dspace/bitstream/2013/319033/14/doi_302677.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:2013/317394,

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"elle 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:2013/296188d,

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-Aël 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:2013/301750b,

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:2013/322914b,

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:2013/312458,

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:2013/316619c,

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

author = {Maarten Jansen},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/316619/3/jansen19ISNPS.pdf},

year  = {2020},

date = {2020-01-01},

journal = {Springer Proceedings in Mathematics and Statistics},

volume = {339},

pages = {249-260},

abstract = {The estimation of a density function with an unknown number of singularities or discontinuities is a typical example of a multiscale problem, with data observed at nonequispaced locations. The data are analyzed through a multiscale local polynomial transform (MLPT), which can be seen as a slightly overcomplete, non-dyadic alternative for a wavelet transform, equipped with the benefits from a local polynomial smoothing procedure. In particular, the multiscale transform adopts a sequence of kernel bandwidths in the local polynomial smoothing as resolution level-dependent, user-controlled scales. The MLPT analysis leads to a reformulation of the problem as a variable selection in a sparse, high-dimensional regression model with exponentially distributed responses. The variable selection is realized by the optimization of the l1-regularized maximum likelihood, where the regularization parameter acts as a threshold. Fine-tuning of the threshold requires the optimization of an information criterion such as AIC. This paper develops discussions on results in[9].},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/316645c,

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

author = {Bastien Marquis and Maarten Jansen},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/316645/3/BMarquis_ISNPS-proc_2.pdf},

year  = {2020},

date = {2020-01-01},

journal = {Springer Proceedings in Mathematics and Statistics},

volume = {339},

pages = {357-365},

abstract = {In sparse high-dimensional data, the selection of a model can lead to an overestimation of the number of nonzero variables. Indeed, the use of an norm constraint while minimising the sum of squared residuals tempers the effects of false positives, thus they are more likely to be included in the model. On the other hand, an regularisation is a non-convex problem and finding its solution is a combinatorial challenge which becomes unfeasible for more than 50 variables. To overcome this situation, one can perform selection via an penalisation but estimate the selected components without shrinkage. This leads to an additional bias in the optimisation of an information criterion over the model size. Used as a stopping rule, this IC must be modified to take into account the deviation of the estimation with and without shrinkage. By looking into the difference between the prediction error and the expected Mallows’s Cp, previous work has analysed a correction for the optimisation bias and an expression can be found for a signal-plus-noise model given some assumptions. A focus on structured models, in particular, grouped variables, shows similar results, though the bias is noticeably reduced.},

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

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:2013/312667,

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 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:2013/296964,

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:2013/294385c,

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 = {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, naïve 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:2013/282177c,

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}

}