Complete List of Works

@article{info:hdl:2013/272529,

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 Fran{c Xavier c}ois 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 = {https://dipot.ulb.ac.be/dspace/bitstream/2013/272529/1/doi_256156.pdf},

year  = {2018},

date = {2018-01-01},

journal = {Acta Neuropathologica},

volume = {135},

number = {2},

pages = {267-283},

abstract = {Although a growing body of evidence indicates that phenotypic plasticity exhibited by glioblastoma cells plays a central role in tumor development and post-therapy recurrence, the master drivers of their aggressiveness remain elusive. Here we mapped the changes in active (H3K4me3) and repressive (H3K27me3) histone modifications accompanying the repression of glioblastoma stem-like cells tumorigenicity. Genes with changing histone marks delineated a network of transcription factors related to cancerous behavior, stem state, and neural development, highlighting a previously unsuspected association between repression of ARNT2 and loss of cell tumorigenicity. Immunohistochemistry confirmed ARNT2 expression in cell sub-populations within proliferative zones of patients' glioblastoma. Decreased ARNT2 expression was consistently observed in non-tumorigenic glioblastoma cells, compared to tumorigenic cells. Moreover, ARNT2 expression correlated with a tumorigenic molecular signature at both the tissue level within the tumor core and at the single cell level in the patients' tumors. We found that ARNT2 knockdown decreased the expression of SOX9, POU3F2 and OLIG2, transcription factors implicated in glioblastoma cell tumorigenicity, and repressed glioblastoma stem-like cell tumorigenic properties in vivo. Our results reveal ARNT2 as a pivotal component of the glioblastoma cell tumorigenic signature, located at a node of a transcription factor network controlling glioblastoma cell aggressiveness.},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/282216,

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/2013/282216/4/438721v1.full.pdf},

year  = {2018},

date = {2018-01-01},

journal = {BioRxiv},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/268207,

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 van Gisbergen and Marc Dalod and Fran{c c}ois Fuks and Stanislas Goriely and Arnaud Marchant},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/268207/1/doi_251834.pdf},

year  = {2018},

date = {2018-01-01},

journal = {eLife},

volume = {7},

abstract = {Cytotoxic CD4 (CD4CTX) T cells are emerging as an important component of anti-viral and anti-tumor immunity but the molecular basis of their development remains poorly understood. In the context of human cytomegalovirus infection, a significant proportion of CD4 T cells displays cytotoxic functions. We observed that the transcriptional program of these cells was enriched in CD8 T cell lineage genes despite the absence of ThPOK downregulation. We further show that establishment of CD4CTX-specific transcriptional and epigenetic programs occurred in a stepwise fashion along the Th1-differentiation pathway. In vitro, prolonged activation of naive CD4 T cells in presence of Th1 polarizing cytokines led to the acquisition of perforin-dependent cytotoxic activity. This process was dependent on the Th1 transcription factor Runx3 and was limited by the sustained expression of ThPOK. This work elucidates the molecular program of human CD4CTXT cells and identifies potential targets for immunotherapy against viral infections and cancer.},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/272668,

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},

abstract = {The Sahara silver ant Cataglyphis bombycina is one of the world's most thermotolerant animals. Workers forage for heat-stricken arthropods during the hottest part of the day, when temperatures exceed 50 $,^circ$C. However, the physiological adaptations needed to cope with such harsh conditions remain poorly studied in this desert species. Using transcriptomics, we screened for the most heat-responsive transcripts of C. bombycina with aim to better characterize the molecular mechanisms involved with macromolecular stability and cell survival to heat-stress. We identified 67 strongly and consistently expressed transcripts, and we show evidences of both evolutionary selection and specific heat-induction of mitochondrial-related molecular chaperones that have not been documented in Formicidae so far. This indicates clear focus of the silver ant's heat-shock response in preserving mitochondrial integrity and energy production. The joined induction of small heat-shock proteins likely depicts the higher requirement of this insect for proper motor function in response to extreme burst of heat-stresses. We discuss how those physiological adaptations may effectively help workers resist and survive the scorching heat and burning ground of the midday Sahara Desert.},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/296973,

title = {Dynamic weights in multi-objective deep reinforcement learning},

author = {Axel Abels and Diederik D M Roijers and Tom Lenaerts},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/296973/3/abels2018bnaic.pdf},

year  = {2018},

date = {2018-01-01},

journal = {BNAIC},

pages = {1-2},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/258224,

title = {Credit Card Fraud Detection: A Realistic Modeling and a Novel Learning Strategy},

author = {Andrea Dal Pozzolo and Giacomo Boracchi and Olivier Caelen and Cesare Alippi and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/258224},

year  = {2017},

date = {2017-01-01},

journal = {IEEE Transactions on Neural Networks and Learning Systems},

volume = {99},

abstract = {Detecting frauds in credit card transactions is perhaps one of the best testbeds for computational intelligence algorithms. In fact, this problem involves a number of relevant challenges, namely: concept drift (customers' habits evolve and fraudsters change their strategies over time), class imbalance (genuine transactions far outnumber frauds), and verification latency (only a small set of transactions are timely checked by investigators). However, the vast majority of learning algorithms that have been proposed for fraud detection rely on assumptions that hardly hold in a real-world fraud-detection system (FDS). This lack of realism concerns two main aspects: 1) the way and timing with which supervised information is provided and 2) the measures used to assess fraud-detection performance. This paper has three major contributions. First, we propose, with the help of our industrial partner, a formalization of the fraud-detection problem that realistically describes the operating conditions of FDSs that everyday analyze massive streams of credit card transactions. We also illustrate the most appropriate performance measures to be used for fraud-detection purposes. Second, we design and assess a novel learning strategy that effectively addresses class imbalance, concept drift, and verification latency. Third, in our experiments, we demonstrate the impact of class unbalance and concept drift in a real-world data stream containing more than 75 million transactions, authorized over a time window of three years.},

note = {DOI: 10.1109/TNNLS.2017.2736643},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/260704,

title = {CancerSubtypes: An R/Bioconductor package for molecular cancer subtype identification, validation and visualization},

author = {Taosheng Xu and Thuc Duy Le and Lin Liu and Ning Su and Rujing Wang and Bingyu Sun and Antonio Colaprico and Gianluca Bontempi and Jiuyong Li},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/260704/1/doi_244331.pdf},

year  = {2017},

date = {2017-01-01},

journal = {Bioinformatics},

volume = {33},

number = {19},

pages = {3131-3133},

abstract = {Summary Identifying molecular cancer subtypes from multi-omics data is an important step in the personalized medicine. We introduce CancerSubtypes, an R package for identifying cancer subtypes using multi-omics data, including gene expression, miRNA expression and DNA methylation data. CancerSubtypes integrates four main computational methods which are highly cited for cancer subtype identification and provides a standardized framework for data pre-processing, feature selection, and result follow-up analyses, including results computing, biology validation and visualization. The input and output of each step in the framework are packaged in the same data format, making it convenience to compare different methods. The package is useful for inferring cancer subtypes from an input genomic dataset, comparing the predictions from different well-known methods and testing new subtype discovery methods, as shown with different application scenarios in theSupplementary Material.},

note = {DOI: 10.1093/bioinformatics/btx378},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/244657,

title = {FOXP1 is a regulator of quiescence in healthy human CD4+ T cells and is constitutively repressed in T cells from patients with lymphoproliferative disorders},

author = {Soizic Garaud and Florence Roufosse and Pushpamali De Silva and Chunyan Gu-Trantien and Jean Nicolas Lodewyckx and Hugues Duvillier and Sarah Dedeurwaerder and Martin Bizet and Matthieu Defrance and Fran{c c}ois Fuks and Fran{c c}oise Bex and Karen Willard-Gallo},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/244657/3/244657.pdf},

year  = {2017},

date = {2017-01-01},

journal = {European Journal of Immunology},

volume = {47},

number = {1},

pages = {168-179},

abstract = {The forkhead box P1 (FOXP1) transcription factor has been shown to regulate the generation and maintenance of quiescent na"ive murine T cells. In humans, FOXP1 expression has been correlated with overall survival in patients with peripheral T-cell lymphoma (PTCL), although its regulatory role in T-cell function is currently unknown. We found that FOXP1 is normally expressed in all human leukocyte subpopulations. Focusing on primary human CD4+ T cells, we show that nuclear expression of FOXP1 predominates in na"ive cells with significant downregulation detected in memory cells from blood and tonsils. FOXP1 is repressed following in vitro T-cell activation of na"ive T cells, and later re-established in memory CD4+ T cells, albeit at lower levels. DNA methylation analysis revealed that epigenetic mechanisms participate in regulating the human FOXP1 gene. ShRNA-mediated FOXP1 repression induces CD4+ T cells to enter the cell cycle, acquire memory-like markers and upregulate helper T-cell differentiation genes. In patients with lymphoproliferative disorders, FOXP1 expression is constitutionally repressed in the clonal T cells in parallel with overexpression of helper T-cell differentiation genes. Collectively, these data identify FOXP1 as an essential transcriptional regulator for primary human CD4+ T cells and suggest its potential important role in the development of PTCL.},

note = {DOI: 10.1002/eji.201646373},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/265312,

title = {DNA methylation-based immune response signature improves patient diagnosis in multiple cancers.},

author = {Jana Jeschke and Martin Bizet and Christine Desmedt and Emilie Calonne and Sarah Dedeurwaerder and Soizic Garaud and Alexander Koch and Denis Larsimont and Roberto Salgado and Gert Van den Eynden and Karen Willard-Gallo and Gianluca Bontempi and Matthieu Defrance and Christos Sotiriou and Fran{c c}ois Fuks},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/265312/6/doi_248939.pdf},

year  = {2017},

date = {2017-01-01},

journal = {The Journal of clinical investigation},

volume = {127},

number = {8},

pages = {3090-3102},

abstract = {The tumor immune response is increasingly associated with better clinical outcomes in breast and other cancers. However, the evaluation of tumor-infiltrating lymphocytes (TILs) relies on histopathological measurements with limited accuracy and reproducibility. Here, we profiled DNA methylation markers to identify a methylation of TIL (MeTIL) signature that recapitulates TIL evaluations and their prognostic value for long-term outcomes in breast cancer (BC).},

note = {DOI: 10.1172/JCI91095},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/258861,

title = {MHC class II expression and potential antigen-presenting cells in the retina during experimental autoimmune uveitis},

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

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/258861/1/doi_242488.pdf},

year  = {2017},

date = {2017-01-01},

journal = {Journal of neuroinflammation},

volume = {14},

number = {1},

abstract = {Background: Controversy exists regarding which cell types are responsible for autoantigen presentation in the retina during experimental autoimmune uveitis (EAU) development. In this study, we aimed to identify and characterize the retinal resident and infiltrating cells susceptible to express major histocompatibility complex (MHC) class II during EAU. Methods: EAU was induced in C57BL/6 mice by adoptive transfer of autoreactive lymphocytes from IRBP1-20-immunized animals. MHC class II expression was studied by immunostainings on eye cryosections. For flow cytometry (FC) analysis, retinas were dissected and enzymatically digested into single-cell suspensions. Three MHC class II+ retinal cell populations were sorted by FC, and their RNA processed for RNA-Seq. Results: Immunostainings demonstrate strong induction of MHC class II expression in EAU, especially in the inner retina at the level of inflamed vessels, extending to the outer retinal layers and the subretinal space in severely inflamed eyes. Most MHC class II+ cells express the hematopoietic marker IBA1. FC quantitative analyses demonstrate that MHC class II induction significantly correlates with disease severity and is associated with upregulation of co-stimulatory molecule expression. In particular, most MHC class IIhi cells express co-stimulatory molecules during EAU. Further phenotyping identified three MHC class II+ retinal cell populations: CD45-CD11b- non-hematopoietic cells with low MHC class II expression and CD45+CD11b+ hematopoietic cells with higher MHC class II expression, which can be further separated into Ly6C+ and Ly6C- cells, possibly corresponding to infiltrating macrophages and resident microglia. Transcriptome analysis of the three sorted populations leads to a clear sample clustering with some enrichment in macrophage markers and microglial cell markers in Ly6C+ and Ly6C- cells, respectively. Functional annotation analysis reveals that both hematopoietic cell populations are more competent in MHC class II-associated antigen presentation and in T cell activation than non-hematopoietic cells. Conclusion: Our results highlight the potential of cells of hematopoietic origin in local antigen presentation, whatever their Ly6C expression. Our work further provides a first transcriptomic study of MHC class II-expressing retinal cells during EAU and delivers a series of new candidate genes possibly implicated in the pathogenesis of retinal autoimmunity.},

note = {DOI: 10.1186/s12974-017-0915-5},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/236112,

title = {Portraying breast cancers with long noncoding RNAs},

author = {Olivier Van Grembergen and Martin Bizet and Eric James de Bony and Emilie Calonne and Pascale Putmans and Sylvain Brohée and Catharina Olsen and Mingzhou Guo and Gianluca Bontempi and Christos Sotiriou and Matthieu Defrance and Fran{c c}ois Fuks},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/236112/1/doi_219739.pdf},

year  = {2016},

date = {2016-01-01},

journal = {Science advances},

volume = {2},

number = {9},

abstract = {Evidence is emerging that long noncoding RNAs (lncRNAs) may play a role in cancer development, but this role is not yet clear. We performed a genome-wide transcriptional survey to explore the lncRNA landscape across 995 breast tissue samples. We identified 215 lncRNAs whose genes are aberrantly expressed in breast tumors, as compared to normal samples. Unsupervised hierarchical clustering of breast tumors on the basis of their lncRNAs revealed four breast cancer subgroups that correlate tightly with PAM50-defined mRNA-based subtypes. Using multivariate analysis, we identified no less than 210 lncRNAs prognostic of clinical outcome. By analyzing the coexpression of lncRNA genes and protein-coding genes, we inferred potential functions of the 215 dysregulated lncRNAs. We then associated subtype-specific lncRNAs with key molecular processes involved in cancer. A correlation was observed, on the one hand, between luminal A--specific lncRNAs and the activation of phosphatidylinositol 3-kinase, fibroblast growth factor, and transforming growth factor--β pathways and, on the other hand, between basal-like--specific lncRNAs and the activation of epidermal growth factor receptor (EGFR)--dependent pathways and of the epithelial-to-mesenchymal transition. Finally, we showed that a specific lncRNA, which we called CYTOR, plays a role in breast cancer. We confirmed its predicted functions, showing that it regulates genes involved in the EGFR/mammalian target of rapamycin pathway and is required for cell proliferation, cell migration, and cytoskeleton organization. Overall, our work provides the most comprehensive analyses for lncRNA in breast cancers. Our findings suggest a wide range of biological functions associated with lncRNAs in breast cancer and provide a foundation for functional investigations that could lead to new therapeutic approaches.},

note = {DOI: 10.1126/sciadv.1600220},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/222877,

title = {TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data.},

author = {Antonio Colaprico and Tiago Da Silva and Catharina Olsen and Luciano Garofano and Claudia Cava and Davide Garolini and Thais TS Sabedot and Tathiane TM Malta and Stefano SM Pagnotta and Isabella Castiglioni and M Ceccarelli and Gianluca Bontempi and Houtan Noushmehr},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/222877/5/doi_206504.pdf},

year  = {2015},

date = {2015-01-01},

journal = {Nucleic acids research},

abstract = {The Cancer Genome Atlas (TCGA) research network has made public a large collection of clinical and molecular phenotypes of more than 10 000 tumor patients across 33 different tumor types. Using this cohort, TCGA has published over 20 marker papers detailing the genomic and epigenomic alterations associated with these tumor types. Although many important discoveries have been made by TCGA's research network, opportunities still exist to implement novel methods, thereby elucidating new biological pathways and diagnostic markers. However, mining the TCGA data presents several bioinformatics challenges, such as data retrieval and integration with clinical data and other molecular data types (e.g. RNA and DNA methylation). We developed an R/Bioconductor package called TCGAbiolinks to address these challenges and offer bioinformatics solutions by using a guided workflow to allow users to query, download and perform integrative analyses of TCGA data. We combined methods from computer science and statistics into the pipeline and incorporated methodologies developed in previous TCGA marker studies and in our own group. Using four different TCGA tumor types (Kidney, Brain, Breast and Colon) as examples, we provide case studies to illustrate examples of reproducibility, integrative analysis and utilization of different Bioconductor packages to advance and accelerate novel discoveries.},

note = {DOI: 10.1093/nar/gkv1507},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/220673,

title = {The bias--variance decomposition in profiled attacks},

author = {Liran Lerman and Gianluca Bontempi and Olivier Markowitch},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/220673},

year  = {2015},

date = {2015-01-01},

journal = {Journal of Cryptographic Engineering},

volume = {5},

number = {4},

pages = {255-267},

abstract = {The profiled attacks challenge the security of cryptographic devices in the worst case scenario. We elucidate the reasons underlying the success of different profiled attacks (that depend essentially on the context) based on the well-known bias--variance tradeoff developed in the machine learning field. Note that our approach can easily be extended to non-profiled attacks. We show (1) how to decompose (in three additive components) the error rate of an attack based on the bias--variance decomposition, and (2) how to reduce the error rate of a model based on the bias--variance diagnostic. Intuitively, we show that different models having the same error rate require different strategies (according to the bias--variance decomposition) to reduce their errors. More precisely, the success rate of a strategy depends on several criteria such as its complexity, the leakage information and the number of points per trace. As a result, a suboptimal strategy in a specific context can lead the adversary to overestimate the security level of the cryptographic device. Our results also bring warnings related to the estimation of the success rate of a profiled attack that can lead the evaluator to underestimate the security level. In brief, certify that a chip leaks (or not) sensitive information represents a hard if not impossible task.},

note = {DOI: 10.1007/s13389-015-0106-1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/223764,

title = {Template attacks vs Machine Learning Revisited},

author = {Liran Lerman and Romain Poussier and Gianluca Bontempi and Olivier Markowitch and Fran{c c}ois-Xavier Standaert},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/223764},

year  = {2015},

date = {2015-01-01},

journal = {Lecture notes in computer science},

volume = {9064},

pages = {20-33},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/205371,

title = {A machine learning approach against a masked AES: Reaching the limit of side-channel attacks with a learning model},

author = {Liran Lerman and Gianluca Bontempi and Olivier Markowitch},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/205371},

year  = {2015},

date = {2015-01-01},

journal = {Journal of Cryptographic Engineering},

volume = {5},

number = {2},

pages = {123-139},

abstract = {Side-channel attacks challenge the security of cryptographic devices. A widespread countermeasure against these attacks is the masking approach. Masking combines sensitive variables with secret random values to reduce its leakage. In 2012, Nassar et al. (DATE, pp 1173--1178. IEEE, 2012) presented a new lightweight (low-cost) boolean masking countermeasure to protect the implementation of the Advanced Encryption Standard (AES) block-cipher. This masking scheme represents the target algorithm of the DPAContest V4 (http://www.dpacontest.org/home/, 2013). In this paper, we present the first machine learning attack against a specific masking countermeasure (more precisely the low-entropy boolean masking countermeasure of Nassar et al.), using the dataset of the DPAContest V4. We succeeded to extract each targeted byte of the key of the masked AES with 7.8 traces during the attacking phase with a strategy based solely on machine learning models. Finally, we compared our proposal with (1) a stochastic attack, (2) a strategy based on template attack and (3) a multivariate regression attack. We show that an attack based on a machine learning model reduces significantly the number of traces required during the attacking step compared to these profiling attacks when analyzing the same leakage information.},

note = {DOI: 10.1007/s13389-014-0089-3},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/205439,

title = {Using shRNA experiments to validate gene regulatory networks},

author = {Catharina Olsen and Kathleen Fleming and Niall Prendergast and Renee Rubio and Frank Emmert-Streib and Gianluca Bontempi and John Quackenbush and Benjamin Haibe-Kains},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/205439/4/doi_189066.pdf},

year  = {2015},

date = {2015-01-01},

journal = {Genomics Data},

volume = {4},

pages = {123-126},

abstract = {Quantitative validation of gene regulatory networks (GRNs) inferred from observational expression data is a difficult task usually involving time intensive and costly laboratory experiments. We were able to show that gene knock-down experiments can be used to quantitatively assess the quality of large-scale GRNs via a purely data-driven approach (Olsen et al. 2014). Our new validation framework also enables the statistical comparison of multiple network inference techniques, which was a long-standing challenge in the field.In this Data in Brief we detail the contents and quality controls for the gene expression data (available from NCBI Gene Expression Omnibus repository with accession number GSE53091) associated with our study published in Genomics (Olsen et al. 2014). We also provide R code to access the data and reproduce the analysis presented in this article.},

note = {DOI: 10.1016/j.gdata.2015.03.011},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/200950,

title = {Ocean plankton. Determinants of community structure in the global plankton interactome.},

author = {Gipsi Lima Mendez and Karoline Faust and Lynn N Henry and Johan Decelle and Simon Colin and Fabrizio Carcillo and Samuel Chaffron and Cesar JC Ignacio-Espinosa and Simon Roux and Flora Vincent and Lucie Bittner and Youssef Darzi and Jun Wang and Stéphane Audic and Léo Berline and Gianluca Bontempi and Ana AM Cabello and Laurent Coppola and Francisco FM Cornejo-Castillo and Francesco d'Ovidio and Luc De Meester and Isabel Ferrera and Marie-José Garet-Delmas and Lionel Guidi and Elena Lara and Stéphane Pesant and Marta Royo-Llonch and Guillem Salazar and Paloma Sanchez and Marta Sebastian and Caroline Souffreau and Céline Dimier and Marc Picheral and Sarah Searson and Stefanie Kandels-Lewis and Tara Oceans coordinators and Gabriel Gorsky and Fabrice Not and Hiroyuki Ogata and Sabrina Speich and Lars Stemmann and Jean Weissenbach and Patrick Wincker and Silvia SG Acinas and Shinichi Sunagawa and Peer Bork and Matthew B Sullivan and Eric Karsenti and Chris Bowler and Colomban de Vargas and Jeroen JR Raes},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/200950},

year  = {2015},

date = {2015-01-01},

journal = {Science},

volume = {348},

number = {6237},

pages = {1262073},

abstract = {Species interaction networks are shaped by abiotic and biotic factors. Here, as part of the Tara Oceans project, we studied the photic zone interactome using environmental factors and organismal abundance profiles and found that environmental factors are incomplete predictors of community structure. We found associations across plankton functional types and phylogenetic groups to be nonrandomly distributed on the network and driven by both local and global patterns. We identified interactions among grazers, primary producers, viruses, and (mainly parasitic) symbionts and validated network-generated hypotheses using microscopy to confirm symbiotic relationships. We have thus provided a resource to support further research on ocean food webs and integrating biological components into ocean models.},

note = {DOI: 10.1126/science.1262073},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/217546,

title = {Integrative Analysis with Monte Carlo Cross-Validation Reveals miRNAs Regulating Pathways Cross-Talk in Aggressive Breast Cancer},

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

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/217546},

year  = {2015},

date = {2015-01-01},

journal = {BioMed Research International},

volume = {2015},

abstract = {In this work an integrated approach was used to identify functional miRNAs regulating gene pathway cross-talk in breast cancer (BC). We first integrated gene expression profiles and biological pathway information to explore the underlying associations between genes differently expressed among normal and BC samples and pathways enriched from these genes. For each pair of pathways, a score was derived from the distribution of gene expression levels by quantifying their pathway cross-talk. Random forest classification allowed the identification of pairs of pathways with high cross-talk. We assessed miRNAs regulating the identified gene pathways by a mutual information analysis. A Fisher test was applied to demonstrate their significance in the regulated pathways. Our results suggest interesting networks of pathways that could be key regulatory of target genes in BC, including stem cell pluripotency, coagulation, and hypoxia pathways and miRNAs that control these networks could be potential biomarkers for diagnostic, prognostic, and therapeutic development in BC. This work shows that standard methods of predicting normal and tumor classes such as differentially expressed miRNAs or transcription factors could lose intrinsic features; instead our approach revealed the responsible molecules of the disease.},

note = {DOI: 10.1155/2015/831314},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/222900,

title = {From dependency to causality: a machine learning approach},

author = {Gianluca Bontempi and Maxime Flauder},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/222900},

year  = {2015},

date = {2015-01-01},

journal = {Journal of machine learning research},

abstract = {The relationship between statistical dependency and causality lies at the heart of all statistical approaches to causal inference. Recent results in the ChaLearn cause-effect pair challenge have shown that causal directionality can be inferred with good accuracy also in Markov indistinguishable configurations thanks to data driven approaches. This paper proposes a supervised machine learning approach to infer the existence of a directed causal link between two variables in multivariate settings with n > 2 variables. The approach relies on the asymmetry of some conditional (in)dependence relations between the members of the Markov blankets of two variables causally connected. Our results show that supervised learning methods may be successfully used to extract causal information on the basis of asymmetric statistical descriptors also for n > 2 variate distributions.},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/226800,

title = {Template attacks vs. Machine learning revisited (and the curse of dimensionality in side-channel analysis)},

author = {Liran Lerman and Romain Poussier and Gianluca Bontempi and Olivier Markowitch and Fran{c c}ois-Xavier Standaert},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/226800},

year  = {2015},

date = {2015-01-01},

journal = {Lecture notes in computer science},

volume = {9064},

pages = {20-33},

abstract = {Template attacks and machine learning are two popular approaches to profiled side-channel analysis. In this paper, we aim to contribute to the understanding of their respective strengths and weaknesses, with a particular focus on their curse of dimensionality. For this purpose, we take advantage of a well-controlled simulated experimental setting in order to put forward two important intuitions. First and from a theoretical point of view, the data complexity of template attacks is not sensitive to the dimension increase in side-channel traces given that their profiling is perfect. Second and from a practical point of view, concrete attacks are always affected by (estimation and assumption) errors during profiling. As these errors increase, machine learning gains interest compared to template attacks, especially when based on random forests.},

note = {DOI: 10.1007/978-3-319-21476-4_2},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/237086,

title = {When is undersampling effective in unbalanced classification tasks?},

author = {Andrea Dal Pozzolo and Olivier Caelen and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/237086},

year  = {2015},

date = {2015-01-01},

journal = {Lecture notes in computer science},

volume = {9284},

pages = {200-215},

abstract = {A well-known rule of thumb in unbalanced classification recommends the rebalancing (typically by resampling) of the classes before proceeding with the learning of the classifier. Though this seems to work for the majority of cases, no detailed analysis exists about the impact of undersampling on the accuracy of the final classifier. This paper aims to fill this gap by proposing an integrated analysis of the two elements which have the largest impact on the effectiveness of an undersampling strategy: the increase of the variance due to the reduction of the number of samples and the warping of the posterior distribution due to the change of priori probabilities. In particular we will propose a theoretical analysis specifying under which conditions undersampling is recommended and expected to be effective. It emerges that the impact of undersampling depends on the number of samples, the variance of the classifier, the degree of imbalance and more specifically on the value of the posterior probability. This makes difficult to predict the average effectiveness of an undersampling strategy since its benefits depend on the distribution of the testing points. Results from several synthetic and real-world unbalanced datasets support and validate our findings.},

note = {DOI: 10.1007/978-3-319-23528-8_13},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/198531,

title = {An approach for the evaluation of human activities in physical therapy scenarios},

author = {M P M P Cuellar and Maria Ros and Maria Martin J Bautista and Yann-A{"e}l Le Borgne and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/198531},

year  = {2015},

date = {2015-01-01},

journal = {Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering},

volume = {141},

pages = {401-414},

abstract = {Human activity recognition has been widely studied since the last decade in ambient intelligence scenarios. Remarkable progresses have been made in this domain, especially in research lines such as ambient assisted living, gesture recognition, behaviour detection and classification, etc. Most of the works in the literature focus on activity classification or recognition, prediction of future events, or anomaly detection and prevention. However, it is hard to find approaches that do not only recognize an activity, but also provide an evaluation of its performance according to an optimality criterion. This problem is of special interest in applications such as sports performance evaluation, physical therapy, etc. In this work, we address the problem of the evaluation of such human activities in monitored environments using depth sensors. In particular, we propose a system able to provide an automatic evaluation of the correctness in the performance of activities involving motion, and more specifically, diagnosis exercises in physical therapy.},

note = {DOI: 10.1007/978-3-319-16292-8_29},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/265293,

title = {Genome-wide hydroxymethylcytosine pattern changes in response to oxidative stress.},

author = {Benjamin Delatte and Jana Jeschke and Matthieu Defrance and Martin Bachman and Catherine Creppe and Emilie Calonne and Martin Bizet and Rachel Deplus and Laura Marroqu{'i} and Myriam Libin and Mirunalini Ravichandran and Fran{c c}oise Mascart and Decio L Eizirik and Adele Murrell and Tomasz Piotr Jurkowski and Fran{c c}ois Fuks},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/265293/4/doi_248920.pdf},

year  = {2015},

date = {2015-01-01},

journal = {Scientific reports},

volume = {5},

pages = {12714},

abstract = {The TET enzymes convert methylcytosine to the newly discovered base hydroxymethylcytosine. While recent reports suggest that TETs may play a role in response to oxidative stress, this role remains uncertain, and results lack in vivo models. Here we show a global decrease of hydroxymethylcytosine in cells treated with buthionine sulfoximine, and in mice depleted for the major antioxidant enzymes GPx1 and 2. Furthermore, genome-wide profiling revealed differentially hydroxymethylated regions in coding genes, and intriguingly in microRNA genes, both involved in response to oxidative stress. These results thus suggest a profound effect of in vivo oxidative stress on the global hydroxymethylome.},

note = {DOI: 10.1038/srep12714},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/262159,

title = {Sox9 Controls Self-Renewal of Oncogene Targeted Cells and Links Tumor Initiation and Invasion.},

author = {Jean-Christophe Larsimont and Youssef Khalil Kass and Adriana Sanchez Danes and Vijayakumar Sukumaran and Matthieu Defrance and Benjamin Delatte and Mélanie Liagre and Pieter Baatsen and Jean-Christophe Marine and Saskia Lippens and Christopher Guerin and Véronique Del Marmol and Jean-Marie Vanderwinden and Fran{c c}ois Fuks and Cédric Blanpain},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/262159/1/Elsevier_245786.pdf},

year  = {2015},

date = {2015-01-01},

journal = {Cell stem cell},

volume = {17},

number = {1},

pages = {60-73},

abstract = {Sox9 is a transcription factor expressed in most solid tumors. However, the molecular mechanisms underlying Sox9 function during tumorigenesis remain unclear. Here, using a genetic mouse model of basal cell carcinoma (BCC), the most frequent cancer in humans, we show that Sox9 is expressed from the earliest step of tumor formation in a Wnt/β-catenin-dependent manner. Deletion of Sox9 together with the constitutive activation of Hedgehog signaling completely prevents BCC formation and leads to a progressive loss of oncogene-expressing cells. Transcriptional profiling of oncogene-expressing cells with Sox9 deletion, combined with in vivo ChIP sequencing, uncovers a cancer-specific gene network regulated by Sox9 that promotes stemness, extracellular matrix deposition, and cytoskeleton remodeling while repressing epidermal differentiation. Our study identifies the molecular mechanisms regulated by Sox9 that link tumor initiation and invasion.},

note = {DOI: 10.1016/j.stem.2015.05.008},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/237115,

title = {RSAT 2015: Regulatory sequence analysis tools},

author = {Alejandra Medina-Rivera and Matthieu Defrance and Olivier Sand and Carl Herrmann and Jaime Abraham Castro-Mondragon and Jeremy Delerce and Sébastien Jaeger and Christophe Blanchet and Pierre Vincens and Christophe Caron and Daniel Michael Ichael D M Staines and Bruno Contreras-Moreira and Marie Artufel and Lucie Charbonnier-Khamvongsa and Céline Hernandez and Denis Thieffry and Morgane Thomas-Chollier and Jacques van Helden},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/237115},

year  = {2015},

date = {2015-01-01},

journal = {Nucleic acids research},

volume = {43},

number = {W1},

pages = {W50-W56},

abstract = {RSAT (Regulatory Sequence Analysis Tools) is a modular software suite for the analysis of cisregulatory elements in genome sequences. Its main applications are (i) motif discovery, appropriate to genome-wide data sets like ChIP-seq, (ii) transcription factor binding motif analysis (quality assessment, comparisons and clustering), (iii) comparative genomics and (iv) analysis of regulatory variations. Nine new programs have been added to the 43 described in the 2011 NAR Web Software Issue, including a tool to extract sequences from a list of coordinates (fetch-sequences from UCSC), novel programs dedicated to the analysis of regulatory variants from GWAS or population genomics (retrieve-variationseq and variation-scan), a program to cluster motifs and visualize the similarities as trees (matrixclustering). To deal with the drastic increase of sequenced genomes, RSAT public sites have been reorganized into taxon-specific servers. The suite is well-documented with tutorials and published protocols. The software suite is available through Web sites, SOAP/WSDL Web services, virtual machines and stand-alone programs at http://www.rsat.eu/.},

note = {DOI: 10.1093/nar/gkv362},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/262160,

title = {5-hydroxymethylcytosine marks promoters in colon that resist DNA hypermethylation in cancer.},

author = {Santiago Uribe-Lewis and Rory Stark and Thomas Carroll and Mark J Dunning and Martin Bachman and Yoko Ito and Lovorka Stojic and Silvia Halim and Sarah L Vowler and Andy G Lynch and Benjamin Delatte and Eric James de Bony and Laurence Colin and Matthieu Defrance and Felix Krueger and Ana Luisa Silva and Rogier ten Hoopen and Ashraf Ek Ibrahim and Adele Murrell and Fran{c c}ois Fuks},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/262160/4/doi_245787.pdf},

year  = {2015},

date = {2015-01-01},

journal = {Genome biology},

volume = {16},

pages = {69},

abstract = {The discovery of cytosine hydroxymethylation (5hmC) as a mechanism that potentially controls DNA methylation changes typical of neoplasia prompted us to investigate its behaviour in colon cancer. 5hmC is globally reduced in proliferating cells such as colon tumours and the gut crypt progenitors, from which tumours can arise.},

note = {DOI: 10.1186/s13059-015-0605-5},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/186425,

title = {From protein sequence to dynamics and disorder with DynaMine.},

author = {Elisa Cilia and Rita Pancsa and Peter Tompa and Tom Lenaerts and Wim Vranken},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/186425/3/doi_170052.pdf},

year  = {2013},

date = {2013-01-01},

journal = {Nature communications},

volume = {4},

pages = {2741},

abstract = {Protein function and dynamics are closely related; however, accurate dynamics information is difficult to obtain. Here based on a carefully assembled data set derived from experimental data for proteins in solution, we quantify backbone dynamics properties on the amino-acid level and develop DynaMine--a fast, high-quality predictor of protein backbone dynamics. DynaMine uses only protein sequence information as input and shows great potential in distinguishing regions of different structural organization, such as folded domains, disordered linkers, molten globules and pre-structured binding motifs of different sizes. It also identifies disordered regions within proteins with an accuracy comparable to the most sophisticated existing predictors, without depending on prior disorder knowledge or three-dimensional structural information. DynaMine provides molecular biologists with an important new method that grasps the dynamical characteristics of any protein of interest, as we show here for human p53 and E1A from human adenovirus 5.},

note = {DOI: 10.1038/ncomms3741},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/155962,

title = {Good agreements make good friends.},

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

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/155962/4/doi_140875.pdf},

year  = {2013},

date = {2013-01-01},

journal = {Scientific reports},

volume = {3},

pages = {2695},

abstract = {When starting a new collaborative endeavor, it pays to establish upfront how strongly your partner commits to the common goal and what compensation can be expected in case the collaboration is violated. Diverse examples in biological and social contexts have demonstrated the pervasiveness of making prior agreements on posterior compensations, suggesting that this behavior could have been shaped by natural selection. Here, we analyze the evolutionary relevance of such a commitment strategy and relate it to the costly punishment strategy, where no prior agreements are made. We show that when the cost of arranging a commitment deal lies within certain limits, substantial levels of cooperation can be achieved. Moreover, these levels are higher than that achieved by simple costly punishment, especially when one insists on sharing the arrangement cost. Not only do we show that good agreements make good friends, agreements based on shared costs result in even better outcomes.},

note = {DOI: 10.1038/srep02695},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/138049,

title = {On the dynamics of neutral mutations in a mathematical model for a homogeneous stem cell population.},

author = {Arne Traulsen and Tom Lenaerts and Jorge J M Pacheco and David Dingli},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/138049},

year  = {2013},

date = {2013-01-01},

journal = {Journal of the Royal Society, Interface / the Royal Society},

volume = {10},

number = {79},

pages = {20120810},

abstract = {The theory of the clonal origin of cancer states that a tumour arises from one cell that acquires mutation(s) leading to the malignant phenotype. It is the current belief that many of these mutations give a fitness advantage to the mutant population allowing it to expand, eventually leading to disease. However, mutations that lead to such a clonal expansion need not give a fitness advantage and may in fact be neutral-or almost neutral-with respect to fitness. Such mutant clones can be eliminated or expand stochastically, leading to a malignant phenotype (disease). Mutations in haematopoietic stem cells give rise to diseases such as chronic myeloid leukaemia (CML) and paroxysmal nocturnal haemoglobinuria (PNH). Although neutral drift often leads to clonal extinction, disease is still possible, and in this case, it has important implications both for the incidence of disease and for therapy, as it may be more difficult to eliminate neutral mutations with therapy. We illustrate the consequences of such dynamics, using CML and PNH as examples. These considerations have implications for many other tumours as well.},

note = {DOI: 10.1098/rsif.2012.0810},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/177704b,

title = {Genome-wide gene expression profiling to predict resistance to anthracyclines in breast cancer patients},

author = {Benjamin Haibe-Kains and Christine Desmedt and Angelo Di Leo and Evandro Azambuja and Denis Larsimont and Jean Selleslags and Suzette Delaloge and Caroline Duhem and Jean-Pierre Kains and Birgit Carly and Marie Maerevoet and Anita Vindevoghel and Ghizlane Rouas and Franccoise Lallemand and Virginie Durbecq and Fatima Cardoso and Roberto Salgado and Rodrigo Kraft Rovere and Gianluca Bontempi and Stefan Michiels and Marc Buyse and Jean-Marie Nogaret and Yuan Qi and William Fraser Symmans and Lajos Pusztai and Veronique D'Hondt and Martine Piccart-Gebhart and Christos Sotiriou},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/177704},

year  = {2013},

date = {2013-01-01},

journal = {Genomics Data},

volume = {1},

pages = {7-10},

note = {DOI: 10.1016/j.gdata.2013.09.001},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/186425b,

title = {From protein sequence to dynamics and disorder with DynaMine.},

author = {Elisa Cilia and Rita Pancsa and Peter Tompa and Tom Lenaerts and Wim Vranken},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/186425},

year  = {2013},

date = {2013-01-01},

journal = {Nature communications},

volume = {4},

pages = {2741},

note = {DOI: 10.1038/ncomms3741},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/151908b,

title = {Management and interpretation of medical data related to cerebral pasly: the ICT4 Rehab project},

author = {Bruno Bonnechere and Vanessa Wermenbol and Bernard Dan and Patrick Salvia and Yann-A"el Le Borgne and Gianluca Bontempi and Stijn Vansummeren and Victor Sholukha and Fedor Moiseev and Bart Jansen and Marcel Rooze and Serge Van Sint Jan},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/151908},

year  = {2013},

date = {2013-01-01},

journal = {European journal of paediatric neurology},

volume = {17},

number = {1},

pages = {32},

note = {Language of publication: na},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/145203b,

title = {Comparison and validation of genomic predictors for anticancer drug sensitivity.},

author = {Simon Papillon-Cavanagh and Nicolas De Jay and Nehme Hachem and Catharina Olsen and Gianluca Bontempi and Hugo J W L Aerts and John Quackenbush and Benjamin Haibe-Kains},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/145203},

year  = {2013},

date = {2013-01-01},

journal = {Journal of the American Medical Informatics Association},

volume = {20},

number = {4},

pages = {597-602},

note = {DOI: 10.1136/amiajnl-2012-001442},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/138049b,

title = {On the dynamics of neutral mutations in a mathematical model for a homogeneous stem cell population.},

author = {Arne Traulsen and Tom Lenaerts and Jorge J. M. Pacheco and David Dingli},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/138049},

year  = {2013},

date = {2013-01-01},

journal = {Journal of the Royal Society, Interface / the Royal Society},

volume = {10},

number = {79},

pages = {20120810},

note = {DOI: 10.1098/rsif.2012.0810},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/155962b,

title = {Good agreements make good friends.},

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

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/155962},

year  = {2013},

date = {2013-01-01},

journal = {Scientific reports},

volume = {3},

pages = {2695},

note = {DOI: 10.1038/srep02695},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/297043b,

title = {Why is it so hard to say sorry?},

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:2013/297043},

year  = {2013},

date = {2013-01-01},

journal = {BNAIC},

pages = {322-323},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/167761b,

title = {Machine learning strategies for time series forecasting},

author = {Gianluca Bontempi and Souhaib Ben Taieb and Yann-A"el Le Borgne},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/167761},

year  = {2013},

date = {2013-01-01},

journal = {Lecture Notes in Business Information Processing},

volume = {138 LNBIP},

pages = {62-77},

note = {DOI: 10.1007/978-3-642-36318-4_3},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/168524b,

title = {Experimental assessment of static and dynamic algorithms for gene regulation inference from time series expression data},

author = {Miguel Lopes and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/168524},

year  = {2013},

date = {2013-01-01},

journal = {Frontiers in Genetics},

volume = {4},

number = {DEC},

note = {DOI: 10.3389/fgene.2013.00303},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/183221b,

title = {A time series approach for profiling attack},

author = {Liran Lerman and Olivier Markowitch and Gianluca Bontempi and Souhaib Ben Taieb},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/183221},

year  = {2013},

date = {2013-01-01},

journal = {Lecture notes in computer science},

volume = {8204},

pages = {75-94},

note = {DOI: 10.1007/978-3-642-41224-0_7},

keywords = {},

pubstate = {published},

tppubtype = {article}

}