2019
|
Coppens, Youri; Efthymiadis, Kyriakos; Lenaerts, Tom; Nowé, Ann Distilling Deep Reinforcement Learning Policies in Soft Decision Trees Proceedings Article In: Miller, Tim; Weber, Rosina; Magazzeni, Daniele (Ed.): Proceedings of the IJCAI 2019 Workshop on Explainable Artificial Intelligence, 2019, (Conference: (Macau, China)). @inproceedings{info:hdl:2013/302065,
title = {Distilling Deep Reinforcement Learning Policies in Soft Decision Trees},
author = {Youri Coppens and Kyriakos Efthymiadis and Tom Lenaerts and Ann Nowé},
editor = {Tim Miller and Rosina Weber and Daniele Magazzeni},
url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/302065/3/xrl.pdf},
year = {2019},
date = {2019-01-01},
booktitle = {Proceedings of the IJCAI 2019 Workshop on Explainable Artificial Intelligence},
abstract = {An important step in Reinforcement Learning (RL) research is to create mechanisms that give higher level insights into the black-box policy models used nowadays and provide explanations for these learned behaviors or motivate the choices behind certain decision steps. In this paper, we illustrate how Soft Decision Tree (SDT) distillation can be used to make policies that are learned through RL more interpretable. Soft Decision Trees create binary trees of predetermined depth, where each branching node represents a hierarchical filter that influences the classification of input data. We distill SDTs from a deep neural network RL policy for the Mario AI benchmark and inspect the learned hierarchy of filters, showing which input features lead to specific action distributions in the episode. We realize preliminary steps towards interpreting the learned behavior of the policy and discuss future improvements.},
note = {Conference: (Macau, China)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
An important step in Reinforcement Learning (RL) research is to create mechanisms that give higher level insights into the black-box policy models used nowadays and provide explanations for these learned behaviors or motivate the choices behind certain decision steps. In this paper, we illustrate how Soft Decision Tree (SDT) distillation can be used to make policies that are learned through RL more interpretable. Soft Decision Trees create binary trees of predetermined depth, where each branching node represents a hierarchical filter that influences the classification of input data. We distill SDTs from a deep neural network RL policy for the Mario AI benchmark and inspect the learned hierarchy of filters, showing which input features lead to specific action distributions in the episode. We realize preliminary steps towards interpreting the learned behavior of the policy and discuss future improvements. |
Abels, Axel; Roijers, Diederik D M; Lenaerts, Tom; Nowe, Ann; Steckelmacher, Denis Dynamic Weights in Multi-Objective Deep Reinforcement Learning Proceedings Article In: Proceedings of the 36th International Conference on Machine Learning, pp. 11-20, PMLR, 2019, (Language of publication: en). @inproceedings{info:hdl:2013/291979,
title = {Dynamic Weights in Multi-Objective Deep Reinforcement Learning},
author = {Axel Abels and Diederik D M Roijers and Tom Lenaerts and Ann Nowe and Denis Steckelmacher},
url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/291979/3/abels19a.pdf},
year = {2019},
date = {2019-01-01},
booktitle = {Proceedings of the 36th International Conference on Machine Learning},
pages = {11-20},
publisher = {PMLR},
series = {Proceedings of Machine Learning Research},
note = {Language of publication: en},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Stefani, Jacopo De; Bontempi, Gianluca; Caelen, Olivier; Hattab, Dalila SYSTEM AND METHOD FOR MANAGING RISKS IN A PROCESS Miscellaneous 2019, (Language of publication: fr). @misc{info:hdl:2013/283233,
title = {SYSTEM AND METHOD FOR MANAGING RISKS IN A PROCESS},
author = {Jacopo De Stefani and Gianluca Bontempi and Olivier Caelen and Dalila Hattab},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/283233},
year = {2019},
date = {2019-01-01},
abstract = {The invention relates to a system and a method for managing risk in a process of an industrial production chain, said system comprising at least one database containing at least one set of time series of raw data relating to said process, a set of devices storing at least one module or a set of modules, the execution of which makes it possible to implement the risk management method comprising at least the preprocessing of a set of raw data so as to produce a set of "proxies" of volatility, the analysis of correlations between the "proxies", the identification of at least one model and of optimal parameters depending at least on said "proxies" and the calculation of the predictions of the set of the "proxies" comprising the combination of at least one of said "proxies" with at least one exogenous parameter included in said set of "proxies".},
note = {Language of publication: fr},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
The invention relates to a system and a method for managing risk in a process of an industrial production chain, said system comprising at least one database containing at least one set of time series of raw data relating to said process, a set of devices storing at least one module or a set of modules, the execution of which makes it possible to implement the risk management method comprising at least the preprocessing of a set of raw data so as to produce a set of "proxies" of volatility, the analysis of correlations between the "proxies", the identification of at least one model and of optimal parameters depending at least on said "proxies" and the calculation of the predictions of the set of the "proxies" comprising the combination of at least one of said "proxies" with at least one exogenous parameter included in said set of "proxies". |
Bontempi, Gianluca The Induction Problem: A Machine Learning Vindication Argument Journal Article In: Lecture notes in computer science, vol. 11943 LNCS, pp. 232-243, 2019, (DOI: 10.1007/978-3-030-37599-7_20). @article{info:hdl:2013/303320,
title = {The Induction Problem: A Machine Learning Vindication Argument},
author = {Gianluca Bontempi},
url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/303320/3/lod2.pdf},
year = {2019},
date = {2019-01-01},
journal = {Lecture notes in computer science},
volume = {11943 LNCS},
pages = {232-243},
abstract = {The problem of induction is a central problem in philosophy of science and concerns whether it is sound or not to extract laws from observational data. Nowadays, this issue is more relevant than ever given the pervasive and growing role of the data discovery process in all sciences. If on one hand induction is routinely employed by automatic machine learning techniques, on the other most of the philosophical work criticises induction as if an alternative could exist. But is there indeed a reliable alternative to induction? Is it possible to discover or predict something in a non inductive manner? This paper formalises the question on the basis of statistical notions (bias, variance, mean squared error) borrowed from estimation theory and statistical machine learning. The result is a justification of induction as rational behaviour. In a decision-making process a behaviour is rational if it is based on making choices that result in the most optimal level of benefit or utility. If we measure utility in a prediction context in terms of expected accuracy, it follows that induction is the rational way of conduct.},
note = {DOI: 10.1007/978-3-030-37599-7_20},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The problem of induction is a central problem in philosophy of science and concerns whether it is sound or not to extract laws from observational data. Nowadays, this issue is more relevant than ever given the pervasive and growing role of the data discovery process in all sciences. If on one hand induction is routinely employed by automatic machine learning techniques, on the other most of the philosophical work criticises induction as if an alternative could exist. But is there indeed a reliable alternative to induction? Is it possible to discover or predict something in a non inductive manner? This paper formalises the question on the basis of statistical notions (bias, variance, mean squared error) borrowed from estimation theory and statistical machine learning. The result is a justification of induction as rational behaviour. In a decision-making process a behaviour is rational if it is based on making choices that result in the most optimal level of benefit or utility. If we measure utility in a prediction context in terms of expected accuracy, it follows that induction is the rational way of conduct. |
Carcillo, Fabrizio; Borgne, Yann-A"el Le; Caelen, Olivier; Kessaci, Yacine; Oblé, Frédéric; Bontempi, Gianluca Combining unsupervised and supervised learning in credit card fraud detection Journal Article In: Information sciences, 2019, (DOI: 10.1016/j.ins.2019.05.042). @article{info:hdl:2013/289125,
title = {Combining unsupervised and supervised learning in credit card fraud detection},
author = {Fabrizio Carcillo and Yann-A{"e}l Le Borgne and Olivier Caelen and Yacine Kessaci and Frédéric Oblé and Gianluca Bontempi},
url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/289125/1/Elsevier_272752.pdf},
year = {2019},
date = {2019-01-01},
journal = {Information sciences},
abstract = {Supervised learning techniques are widely employed in credit card fraud detection, as they make use of the assumption that fraudulent patterns can be learned from an analysis of past transactions. The task becomes challenging, however, when it has to take account of changes in customer behavior and fraudsters' ability to invent novel fraud patterns. In this context, unsupervised learning techniques can help the fraud detection systems to find anomalies. In this paper we present a hybrid technique that combines supervised and unsupervised techniques to improve the fraud detection accuracy. Unsupervised outlier scores, computed at different levels of granularity, are compared and tested on a real, annotated, credit card fraud detection dataset. Experimental results show that the combination is efficient and does indeed improve the accuracy of the detection.},
note = {DOI: 10.1016/j.ins.2019.05.042},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Supervised learning techniques are widely employed in credit card fraud detection, as they make use of the assumption that fraudulent patterns can be learned from an analysis of past transactions. The task becomes challenging, however, when it has to take account of changes in customer behavior and fraudsters' ability to invent novel fraud patterns. In this context, unsupervised learning techniques can help the fraud detection systems to find anomalies. In this paper we present a hybrid technique that combines supervised and unsupervised techniques to improve the fraud detection accuracy. Unsupervised outlier scores, computed at different levels of granularity, are compared and tested on a real, annotated, credit card fraud detection dataset. Experimental results show that the combination is efficient and does indeed improve the accuracy of the detection. |
Bontempi, Gianluca Comments on M4 competition Journal Article In: International journal of forecasting, 2019, (DOI: 10.1016/j.ijforecast.2019.03.028). @article{info:hdl:2013/292419,
title = {Comments on M4 competition},
author = {Gianluca Bontempi},
url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/292419/1/Elsevier_276046.pdf},
year = {2019},
date = {2019-01-01},
journal = {International journal of forecasting},
note = {DOI: 10.1016/j.ijforecast.2019.03.028},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Mounir, Mohamed; Lucchetta, Marta; Silva, Tiago Henrique Da T C; Olsen, Catharina; Bontempi, Gianluca; Chen, Xi; Noushmehr, Houtan; Colaprico, Antonio; Papaleo, Elena New functionalities in the TCGAbiolinks package for the study and integration of cancer data from GDC and GTEx Journal Article In: PLoS computational biology, vol. 15, no. 3, pp. e1006701, 2019, (DOI: 10.1371/journal.pcbi.1006701). @article{info:hdl:2013/286948,
title = {New functionalities in the TCGAbiolinks package for the study and integration of cancer data from GDC and GTEx},
author = {Mohamed Mounir and Marta Lucchetta and Tiago Henrique Da T C Silva and Catharina Olsen and Gianluca Bontempi and Xi Chen and Houtan Noushmehr and Antonio Colaprico and Elena Papaleo},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/286948},
year = {2019},
date = {2019-01-01},
journal = {PLoS computational biology},
volume = {15},
number = {3},
pages = {e1006701},
abstract = {The advent of Next-Generation Sequencing (NGS) technologies has opened new perspectives in deciphering the genetic mechanisms underlying complex diseases. Nowadays, the amount of genomic data is massive and substantial efforts and new tools are required to unveil the information hidden in the data. The Genomic Data Commons (GDC) Data Portal is a platform that contains different genomic studies including the ones from The Cancer Genome Atlas (TCGA) and the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiatives, accounting for more than 40 tumor types originating from nearly 30000 patients. Such platforms, although very attractive, must make sure the stored data are easily accessible and adequately harmonized. Moreover, they have the primary focus on the data storage in a unique place, and they do not provide a comprehensive toolkit for analyses and interpretation of the data. To fulfill this urgent need, comprehensive but easily accessible computational methods for integrative analyses of genomic data that do not renounce a robust statistical and theoretical framework are required. In this context, the R/Bioconductor package TCGAbiolinks was developed, offering a variety of bioinformatics functionalities. Here we introduce new features and enhancements of TCGAbiolinks in terms of i) more accurate and flexible pipelines for differential expression analyses, ii) different methods for tumor purity estimation and filtering, iii) integration of normal samples from other platforms iv) support for other genomics datasets, exemplified here by the TARGET data. Evidence has shown that accounting for tumor purity is essential in the study of tumorigenesis, as these factors promote confounding behavior regarding differential expression analysis. With this in mind, we implemented these filtering procedures in TCGAbiolinks. Moreover, a limitation of some of the TCGA datasets is the unavailability or paucity of corresponding normal samples. We thus integrated into TCGAbiolinks the possibility to use normal samples from the Genotype-Tissue Expression (GTEx) project, which is another large-scale repository cataloging gene expression from healthy individuals. The new functionalities are available in the TCGAbiolinks version 2.8 and higher released in Bioconductor version 3.7.},
note = {DOI: 10.1371/journal.pcbi.1006701},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The advent of Next-Generation Sequencing (NGS) technologies has opened new perspectives in deciphering the genetic mechanisms underlying complex diseases. Nowadays, the amount of genomic data is massive and substantial efforts and new tools are required to unveil the information hidden in the data. The Genomic Data Commons (GDC) Data Portal is a platform that contains different genomic studies including the ones from The Cancer Genome Atlas (TCGA) and the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiatives, accounting for more than 40 tumor types originating from nearly 30000 patients. Such platforms, although very attractive, must make sure the stored data are easily accessible and adequately harmonized. Moreover, they have the primary focus on the data storage in a unique place, and they do not provide a comprehensive toolkit for analyses and interpretation of the data. To fulfill this urgent need, comprehensive but easily accessible computational methods for integrative analyses of genomic data that do not renounce a robust statistical and theoretical framework are required. In this context, the R/Bioconductor package TCGAbiolinks was developed, offering a variety of bioinformatics functionalities. Here we introduce new features and enhancements of TCGAbiolinks in terms of i) more accurate and flexible pipelines for differential expression analyses, ii) different methods for tumor purity estimation and filtering, iii) integration of normal samples from other platforms iv) support for other genomics datasets, exemplified here by the TARGET data. Evidence has shown that accounting for tumor purity is essential in the study of tumorigenesis, as these factors promote confounding behavior regarding differential expression analysis. With this in mind, we implemented these filtering procedures in TCGAbiolinks. Moreover, a limitation of some of the TCGA datasets is the unavailability or paucity of corresponding normal samples. We thus integrated into TCGAbiolinks the possibility to use normal samples from the Genotype-Tissue Expression (GTEx) project, which is another large-scale repository cataloging gene expression from healthy individuals. The new functionalities are available in the TCGAbiolinks version 2.8 and higher released in Bioconductor version 3.7. |
Verhelst, Theo; Caelen, Olivier; Dewitte, Jean Christophe; Lebichot, Bertrand; Bontempi, Gianluca Understanding telecom customer churn with machine learning: From prediction to causal inference Journal Article In: CEUR Workshop Proceedings, vol. 2491, 2019, (Language of publication: en). @article{info:hdl:2013/296511,
title = {Understanding telecom customer churn with machine learning: From prediction to causal inference},
author = {Theo Verhelst and Olivier Caelen and Jean Christophe Dewitte and Bertrand Lebichot and Gianluca Bontempi},
url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/296511/3/abstract28.pdf},
year = {2019},
date = {2019-01-01},
journal = {CEUR Workshop Proceedings},
volume = {2491},
note = {Language of publication: en},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Jansen, Maarten Multiscale local polynomials for unequispaced data processing Miscellaneous 2019, (Conference: FNRS contact group study day ``Wavelets and applications''). @misc{info:hdl:2013/297566,
title = {Multiscale local polynomials for unequispaced data processing},
author = {Maarten Jansen},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/297566},
year = {2019},
date = {2019-01-01},
note = {Conference: FNRS contact group study day ``Wavelets and applications''},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
|
Jansen, Maarten Multiscale local polynomial estimation from highly irregular data Miscellaneous 2019, (Language of publication: fr). @misc{info:hdl:2013/297565,
title = {Multiscale local polynomial estimation from highly irregular data},
author = {Maarten Jansen},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/297565},
year = {2019},
date = {2019-01-01},
note = {Language of publication: fr},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
|
Abels, Axel; Roijers, Diederik D. M.; Lenaerts, Tom; Nowe, Ann; Steckelmacher, Denis Dynamic Weights in Multi-Objective Deep Reinforcement Learning Miscellaneous 2019, (Conference: 36th International Conference on Machine Learning (2019: Long Beach, USA)). @misc{info:hdl:2013/291984,
title = {Dynamic Weights in Multi-Objective Deep Reinforcement Learning},
author = {Axel Abels and Diederik D. M. Roijers and Tom Lenaerts and Ann Nowe and Denis Steckelmacher},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/291984},
year = {2019},
date = {2019-01-01},
note = {Conference: 36th International Conference on Machine Learning (2019: Long Beach, USA)},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
|
Domingos, Elias Fernández; Grujić, Jelena; Burguillo, Juan Carlos; Kirchsteiger, Georg; Santos, Francisco C; Lenaerts, Tom Human reciprocation and polarization in managing of uncertain public goods Miscellaneous 2019, (Conference: ALIFE19 Workshop on Computational Approaches to Social Dynamic: Data, Modeling, Simulation and Hybrids(19: 29/7-2/8/2019: Newcastle, United Kingdom)). @misc{info:hdl:2013/336150,
title = {Human reciprocation and polarization in managing of uncertain public goods},
author = {Elias Fernández Domingos and Jelena Grujić and Juan Carlos Burguillo and Georg Kirchsteiger and Francisco C Santos and Tom Lenaerts},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/336150},
year = {2019},
date = {2019-01-01},
note = {Conference: ALIFE19 Workshop on Computational Approaches to Social Dynamic: Data, Modeling, Simulation and Hybrids(19: 29/7-2/8/2019: Newcastle, United Kingdom)},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
|
Renaux, Alexandre; Papadimitriou, Sofia; Versbraegen, Nassim; Nachtegael, Charlotte; Boutry, Simon; Nowé, Ann; Smits, Guillaume; Lenaerts, Tom Towards oligogenic disease prediction with ORVAL: a web-platform to uncover pathogenic variant combinations Miscellaneous 2019, (Conference: the 27th conference on Intelligent Systems for Molecular Biology (ISMB) and the 18th European Conference on Computational Biology(21-25/7/2019: Basel, Switzerland)). @misc{info:hdl:2013/336176,
title = {Towards oligogenic disease prediction with ORVAL: a web-platform to uncover pathogenic variant combinations},
author = {Alexandre Renaux and Sofia Papadimitriou and Nassim Versbraegen and Charlotte Nachtegael and Simon Boutry and Ann Nowé and Guillaume Smits and Tom Lenaerts},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/336176},
year = {2019},
date = {2019-01-01},
note = {Conference: the 27th conference on Intelligent Systems for Molecular Biology (ISMB) and the 18th European Conference on Computational Biology(21-25/7/2019: Basel, Switzerland)},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
|
Renaux, Alexandre; Papadimitriou, Sofia; Versbraegen, Nassim; Nachtegael, Charlotte; Boutry, Simon; Nowé, Ann; Smits, Guillaume; Lenaerts, Tom Towards oligogenic disease prediction with ORVAL: a web-platform to uncover pathogenic variant combinations Miscellaneous 2019, (Conference: 15th Student Council Symposium at the ISMB/ECCB 2019.(15: 21-25/7/2019: Basel, Switzerland)). @misc{info:hdl:2013/336175,
title = {Towards oligogenic disease prediction with ORVAL: a web-platform to uncover pathogenic variant combinations},
author = {Alexandre Renaux and Sofia Papadimitriou and Nassim Versbraegen and Charlotte Nachtegael and Simon Boutry and Ann Nowé and Guillaume Smits and Tom Lenaerts},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/336175},
year = {2019},
date = {2019-01-01},
note = {Conference: 15th Student Council Symposium at the ISMB/ECCB 2019.(15: 21-25/7/2019: Basel, Switzerland)},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
|
Domingos, Elias Fernández; Santos, Francisco C; Lenaerts, Tom Learning dynamics in uncertain collective endeavors Miscellaneous 2019, (Conference: ALIFE19 Workshop on Evolution of Human Behavior(29: 29/7-2/8/2019: Newcastle, UK)). @misc{info:hdl:2013/336157,
title = {Learning dynamics in uncertain collective endeavors},
author = {Elias Fernández Domingos and Francisco C Santos and Tom Lenaerts},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/336157},
year = {2019},
date = {2019-01-01},
note = {Conference: ALIFE19 Workshop on Evolution of Human Behavior(29: 29/7-2/8/2019: Newcastle, UK)},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
|
Istaces, Nicolas; Splittgerber, Marion; Silva, Viviana Lima; Nguyen, Muriel; Thomas, Séverine; Le, Aurore; Achouri, Younes; Calonne, Emilie; Defrance, Matthieu; cois Fuks, Franc; Goriely, Stanislas; Azouz, Abdulkader EOMES interacts with RUNX3 and BRG1 to promote innate memory cell formation through epigenetic reprogramming Journal Article In: Nature communications, vol. 10, no. 1, 2019, (DOI: 10.1038/s41467-019-11233-6). @article{info:hdl:2013/294385,
title = {EOMES interacts with RUNX3 and BRG1 to promote innate memory cell formation through epigenetic reprogramming},
author = {Nicolas Istaces and Marion Splittgerber and Viviana Lima Silva and Muriel Nguyen and Séverine Thomas and Aurore Le and Younes Achouri and Emilie Calonne and Matthieu Defrance and Fran{c c}ois Fuks and Stanislas Goriely and Abdulkader Azouz},
url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/294385/1/doi_278012.pdf},
year = {2019},
date = {2019-01-01},
journal = {Nature communications},
volume = {10},
number = {1},
abstract = {Memory CD8+ T cells have the ability to provide lifelong immunity against pathogens. Although memory features generally arise after challenge with a foreign antigen, na"ive CD8 single positive (SP) thymocytes may acquire phenotypic and functional characteristics of memory cells in response to cytokines such as interleukin-4. This process is associated with the induction of the T-box transcription factor Eomesodermin (EOMES). However, the underlying molecular mechanisms remain ill-defined. Using epigenomic profiling, we show that these innate memory CD8SP cells acquire only a portion of the active enhancer repertoire of conventional memory cells. This reprograming is secondary to EOMES recruitment, mostly to RUNX3-bound enhancers. Furthermore, EOMES is found within chromatin-associated complexes containing BRG1 and promotes the recruitment of this chromatin remodelling factor. Also, the in vivo acquisition of EOMES-dependent program is BRG1-dependent. In conclusion, our results support a strong epigenetic basis for the EOMES-driven establishment of CD8+ T cell innate memory program.},
note = {DOI: 10.1038/s41467-019-11233-6},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Memory CD8+ T cells have the ability to provide lifelong immunity against pathogens. Although memory features generally arise after challenge with a foreign antigen, na"ive CD8 single positive (SP) thymocytes may acquire phenotypic and functional characteristics of memory cells in response to cytokines such as interleukin-4. This process is associated with the induction of the T-box transcription factor Eomesodermin (EOMES). However, the underlying molecular mechanisms remain ill-defined. Using epigenomic profiling, we show that these innate memory CD8SP cells acquire only a portion of the active enhancer repertoire of conventional memory cells. This reprograming is secondary to EOMES recruitment, mostly to RUNX3-bound enhancers. Furthermore, EOMES is found within chromatin-associated complexes containing BRG1 and promotes the recruitment of this chromatin remodelling factor. Also, the in vivo acquisition of EOMES-dependent program is BRG1-dependent. In conclusion, our results support a strong epigenetic basis for the EOMES-driven establishment of CD8+ T cell innate memory program. |
Saykali, Bechara; Nahaboo, Wallis; Mathiah, Navrita; Racu, Marie-Lucie; Defrance, Matthieu; Migeotte, Isabelle Distinct mesoderm migration phenotypes in extra-embryonic and embryonic regions of the early mouse embryo Journal Article In: eLife, vol. 8, 2019, (DOI: 10.7554/eLife.42434.001). @article{info:hdl:2013/282177,
title = {Distinct mesoderm migration phenotypes in extra-embryonic and embryonic regions of the early mouse embryo},
author = {Bechara Saykali and Wallis Nahaboo and Navrita Mathiah and Marie-Lucie Racu and Matthieu Defrance and Isabelle Migeotte},
url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/282177/3/elife-42434-v1.pdf},
year = {2019},
date = {2019-01-01},
journal = {eLife},
volume = {8},
abstract = {In mouse embryo gastrulation, epiblast cells delaminate at the primitive streak to form mesoderm and definitive endoderm, through an epithelial-mesenchymal transition. Mosaic expression of a membrane reporter in nascent mesoderm enabled recording cell shape and trajectory through live imaging. Upon leaving the streak, cells changed shape and extended protrusions of distinct size and abundance depending on the neighboring germ layer, as well as the region of the embryo. Embryonic trajectories were meandrous but directional, while extra-embryonic mesoderm cells showed little net displacement. Embryonic and extra-embryonic mesoderm transcriptomes highlighted distinct guidance, cytoskeleton, adhesion, and extracellular matrix signatures. Specifically, intermediate filaments were highly expressed in extra-embryonic mesoderm, while live imaging for F-actin showed abundance of actin filaments in embryonic mesoderm only. Accordingly, Rhoa or Rac1 conditional deletion in mesoderm inhibited embryonic, but not extra-embryonic mesoderm migration. Overall, this indicates separate cytoskeleton regulation coordinating the morphology and migration of mesoderm subpopulations.},
note = {DOI: 10.7554/eLife.42434.001},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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. |
Claeskens, G.; Jansen, Maarten Discussion on ``Model Confidence Bounds for Variable Selection'' by Yang Li, Yuetian Luo, Davide Ferrari, Xiaonan Hu, and Yichen Qin Journal Article In: Biometrics, vol. 75, no. 2, pp. 404-406, 2019, (Language of publication: en). @article{info:hdl:2013/280731,
title = {Discussion on ``Model Confidence Bounds for Variable Selection'' by Yang Li, Yuetian Luo, Davide Ferrari, Xiaonan Hu, and Yichen Qin},
author = {G. Claeskens and Maarten Jansen},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/280731},
year = {2019},
date = {2019-01-01},
journal = {Biometrics},
volume = {75},
number = {2},
pages = {404-406},
note = {Language of publication: en},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Claeskens, G.; Jansen, Maarten Discussion on “Model Confidence Bounds for Variable Selection” by Yang Li, Yuetian Luo, Davide Ferrari, Xiaonan Hu, and Yichen Qin Journal Article In: Biometrics, 2019, (DOI: 10.1111/biom.13022). @article{info:hdl:2013/287247,
title = {Discussion on “Model Confidence Bounds for Variable Selection” by Yang Li, Yuetian Luo, Davide Ferrari, Xiaonan Hu, and Yichen Qin},
author = {G. Claeskens and Maarten Jansen},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/287247},
year = {2019},
date = {2019-01-01},
journal = {Biometrics},
note = {DOI: 10.1111/biom.13022},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Istaces, Nicolas; Splittgerber, Marion; Silva, Viviana Lima; Nguyen, Muriel; Thomas, Séverine; Le, Aurore; Achouri, Younes; Calonne, Emilie; Defrance, Matthieu; Fuks, Franccois; Goriely, Stanislas; Azouz, Abdulkader EOMES interacts with RUNX3 and BRG1 to promote innate memory cell formation through epigenetic reprogramming Journal Article In: Nature communications, vol. 10, no. 1, 2019, (DOI: 10.1038/s41467-019-11233-6). @article{info:hdl:2013/294385b,
title = {EOMES interacts with RUNX3 and BRG1 to promote innate memory cell formation through epigenetic reprogramming},
author = {Nicolas Istaces and Marion Splittgerber and Viviana Lima Silva and Muriel Nguyen and Séverine Thomas and Aurore Le and Younes Achouri and Emilie Calonne and Matthieu Defrance and Franccois Fuks and Stanislas Goriely and Abdulkader Azouz},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/294385},
year = {2019},
date = {2019-01-01},
journal = {Nature communications},
volume = {10},
number = {1},
note = {DOI: 10.1038/s41467-019-11233-6},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Versbraegen, Nassim; Fouché, Aziz; Nachtegael, Charlotte; Papadimitriou, Sofia; Gazzo, Andrea; Smits, Guillaume; Lenaerts, Tom Using game theory and decision decomposition to effectively discern and characterise bi-locus diseases Journal Article In: Artificial intelligence in medicine, vol. 99, 2019, (DOI: 10.1016/j.artmed.2019.06.006). @article{info:hdl:2013/292462b,
title = {Using game theory and decision decomposition to effectively discern and characterise bi-locus diseases},
author = {Nassim Versbraegen and Aziz Fouché and Charlotte Nachtegael and Sofia Papadimitriou and Andrea Gazzo and Guillaume Smits and Tom Lenaerts},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/292462},
year = {2019},
date = {2019-01-01},
journal = {Artificial intelligence in medicine},
volume = {99},
note = {DOI: 10.1016/j.artmed.2019.06.006},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Renaux, Alexandre; Papadimitriou, Sofia; Versbraegen, Nassim; Nachtegael, Charlotte; Boutry, Simon; Nowé, Ann; Smits, Guillaume; Lenaerts, Tom ORVAL: a novel platform for the prediction and exploration of disease-causing oligogenic variant combinations. Journal Article In: Nucleic acids research, vol. 47, no. W1, pp. W93-W98, 2019, (DOI: 10.1093/nar/gkz437). @article{info:hdl:2013/289958b,
title = {ORVAL: a novel platform for the prediction and exploration of disease-causing oligogenic variant combinations.},
author = {Alexandre Renaux and Sofia Papadimitriou and Nassim Versbraegen and Charlotte Nachtegael and Simon Boutry and Ann Nowé and Guillaume Smits and Tom Lenaerts},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/289958},
year = {2019},
date = {2019-01-01},
journal = {Nucleic acids research},
volume = {47},
number = {W1},
pages = {W93-W98},
note = {DOI: 10.1093/nar/gkz437},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Papadimitriou, Sofia; Gazzo, Andrea; Versbraegen, Nassim; Nachtegael, Charlotte; Aerts, Jan; Moreau, Yves; Dooren, Sonia Van; Nowe, Ann; Smits, Guillaume; Lenaerts, Tom Predicting disease-causing variant combinations Journal Article In: Proceedings of the National Academy of Sciences of the United States of America, vol. 116, no. 24, pp. 11878-11887, 2019, (DOI: 10.1073/pnas.1815601116). @article{info:hdl:2013/289724b,
title = {Predicting disease-causing variant combinations},
author = {Sofia Papadimitriou and Andrea Gazzo and Nassim Versbraegen and Charlotte Nachtegael and Jan Aerts and Yves Moreau and Sonia Van Dooren and Ann Nowe and Guillaume Smits and Tom Lenaerts},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/289724},
year = {2019},
date = {2019-01-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {116},
number = {24},
pages = {11878-11887},
note = {DOI: 10.1073/pnas.1815601116},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Bontempi, Gianluca The Induction Problem: A Machine Learning Vindication Argument Journal Article In: Lecture notes in computer science, vol. 11943 LNCS, pp. 232-243, 2019, (DOI: 10.1007/978-3-030-37599-7_20). @article{info:hdl:2013/303320b,
title = {The Induction Problem: A Machine Learning Vindication Argument},
author = {Gianluca Bontempi},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/303320},
year = {2019},
date = {2019-01-01},
journal = {Lecture notes in computer science},
volume = {11943 LNCS},
pages = {232-243},
note = {DOI: 10.1007/978-3-030-37599-7_20},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Carcillo, Fabrizio; Borgne, Yann-A"el Le; Caelen, Olivier; Kessaci, Yacine; Oblé, Frédéric; Bontempi, Gianluca Combining unsupervised and supervised learning in credit card fraud detection Journal Article In: Information sciences, 2019, (DOI: 10.1016/j.ins.2019.05.042). @article{info:hdl:2013/289125b,
title = {Combining unsupervised and supervised learning in credit card fraud detection},
author = {Fabrizio Carcillo and Yann-A"el Le Borgne and Olivier Caelen and Yacine Kessaci and Frédéric Oblé and Gianluca Bontempi},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/289125},
year = {2019},
date = {2019-01-01},
journal = {Information sciences},
note = {DOI: 10.1016/j.ins.2019.05.042},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Bontempi, Gianluca Comments on M4 competition Journal Article In: International journal of forecasting, 2019, (DOI: 10.1016/j.ijforecast.2019.03.028). @article{info:hdl:2013/292419b,
title = {Comments on M4 competition},
author = {Gianluca Bontempi},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/292419},
year = {2019},
date = {2019-01-01},
journal = {International journal of forecasting},
note = {DOI: 10.1016/j.ijforecast.2019.03.028},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Saykali, Bechara; Nahaboo, Wallis; Mathiah, Navrita; Racu, Marie-Lucie; Defrance, Matthieu; Migeotte, Isabelle Distinct mesoderm migration phenotypes in extra-embryonic and embryonic regions of the early mouse embryo Journal Article In: eLife, vol. 8, 2019, (DOI: 10.7554/eLife.42434.001). @article{info:hdl:2013/282177b,
title = {Distinct mesoderm migration phenotypes in extra-embryonic and embryonic regions of the early mouse embryo},
author = {Bechara Saykali and Wallis Nahaboo and Navrita Mathiah and Marie-Lucie Racu and Matthieu Defrance and Isabelle Migeotte},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/282177},
year = {2019},
date = {2019-01-01},
journal = {eLife},
volume = {8},
note = {DOI: 10.7554/eLife.42434.001},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Mounir, Mohamed; Lucchetta, Marta; Silva, Tiago Henrique Da T. C.; Olsen, Catharina; Bontempi, Gianluca; Chen, Xi; Noushmehr, Houtan; Colaprico, Antonio; Papaleo, Elena New functionalities in the TCGAbiolinks package for the study and integration of cancer data from GDC and GTEx Journal Article In: PLoS computational biology, vol. 15, no. 3, pp. e1006701, 2019, (DOI: 10.1371/journal.pcbi.1006701). @article{info:hdl:2013/286948b,
title = {New functionalities in the TCGAbiolinks package for the study and integration of cancer data from GDC and GTEx},
author = {Mohamed Mounir and Marta Lucchetta and Tiago Henrique Da T. C. Silva and Catharina Olsen and Gianluca Bontempi and Xi Chen and Houtan Noushmehr and Antonio Colaprico and Elena Papaleo},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/286948},
year = {2019},
date = {2019-01-01},
journal = {PLoS computational biology},
volume = {15},
number = {3},
pages = {e1006701},
note = {DOI: 10.1371/journal.pcbi.1006701},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Libin, Pieter; Versbraegen, Nassim; Abecasis, Ana A. B.; Gomes, Perpétua; Lenaerts, Tom; Nowe, Ann Towards a phylogenetic measure to quantify HIV incidence Journal Article In: CEUR Workshop Proceedings, vol. 2491, 2019, (Language of publication: en). @article{info:hdl:2013/296964b,
title = {Towards a phylogenetic measure to quantify HIV incidence},
author = {Pieter Libin and Nassim Versbraegen and Ana A. B. Abecasis and Perpétua Gomes and Tom Lenaerts and Ann Nowe},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/296964},
year = {2019},
date = {2019-01-01},
journal = {CEUR Workshop Proceedings},
volume = {2491},
note = {Language of publication: en},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Verhelst, Theo; Caelen, Olivier; Dewitte, Jean Christophe; Lebichot, Bertrand; Bontempi, Gianluca Understanding telecom customer churn with machine learning: From prediction to causal inference Journal Article In: CEUR Workshop Proceedings, vol. 2491, 2019, (Language of publication: en). @article{info:hdl:2013/296511b,
title = {Understanding telecom customer churn with machine learning: From prediction to causal inference},
author = {Theo Verhelst and Olivier Caelen and Jean Christophe Dewitte and Bertrand Lebichot and Gianluca Bontempi},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/296511},
year = {2019},
date = {2019-01-01},
journal = {CEUR Workshop Proceedings},
volume = {2491},
note = {Language of publication: en},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
2018
|
Raimondi, Daniele; Orlando, Gabriele; Tabaro, Francesco; Lenaerts, Tom; Rooman, Marianne; Moreau, Yves; Vranken, Wim F Large-scale in-silico statistical mutagenesis analysis sheds light on the deleteriousness landscape of the human proteome. Journal Article In: Scientific reports, vol. 8, no. 1, pp. 16980, 2018, (DOI: 10.1038/s41598-018-34959-7). @article{info:hdl:2013/283645b,
title = {Large-scale in-silico statistical mutagenesis analysis sheds light on the deleteriousness landscape of the human proteome.},
author = {Daniele Raimondi and Gabriele Orlando and Francesco Tabaro and Tom Lenaerts and Marianne Rooman and Yves Moreau and Wim F Vranken},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/283645},
year = {2018},
date = {2018-01-01},
journal = {Scientific reports},
volume = {8},
number = {1},
pages = {16980},
note = {DOI: 10.1038/s41598-018-34959-7},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Stefani, Jacopo De; Borgne, Yann-A"el Le; Caelen, Olivier; Hattab, Dalila; Bontempi, Gianluca Batch and incremental dynamic factor machine learning for multivariate and multi-step-ahead forecasting Journal Article In: International journal of data science and analytics (Print), vol. 7, no. 4, pp. 311-329, 2018, (DOI: 10.1007/s41060-018-0150-x). @article{info:hdl:2013/283230b,
title = {Batch and incremental dynamic factor machine learning for multivariate and multi-step-ahead forecasting},
author = {Jacopo De Stefani and Yann-A"el Le Borgne and Olivier Caelen and Dalila Hattab and Gianluca Bontempi},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/283230},
year = {2018},
date = {2018-01-01},
journal = {International journal of data science and analytics (Print)},
volume = {7},
number = {4},
pages = {311-329},
note = {DOI: 10.1007/s41060-018-0150-x},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Bony, Eric James; Bizet, Martin; Grembergen, Olivier Van; Hassabi, Bouchra; Calonne, Emilie; Putmans, Pascale; Bontempi, Gianluca; Fuks, Franccois Comprehensive identification of long noncoding RNAs in colorectal cancer Journal Article In: Oncotarget, vol. 9, no. 45, pp. 27605-27629, 2018, (DOI: 10.18632/oncotarget.25218). @article{info:hdl:2013/278063b,
title = {Comprehensive identification of long noncoding RNAs in colorectal cancer},
author = {Eric James Bony and Martin Bizet and Olivier Van Grembergen and Bouchra Hassabi and Emilie Calonne and Pascale Putmans and Gianluca Bontempi and Franccois Fuks},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/278063},
year = {2018},
date = {2018-01-01},
journal = {Oncotarget},
volume = {9},
number = {45},
pages = {27605-27629},
note = {DOI: 10.18632/oncotarget.25218},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Carcillo, Fabrizio; Borgne, Yann-A"el Le; Caelen, Olivier; Bontempi, Gianluca Streaming active learning strategies for real-life credit card fraud detection: assessment and visualization Journal Article In: International journal of data science and analytics (Print), vol. 5, no. 4, pp. 285-300, 2018, (DOI: 10.1007/s41060-018-0116-z). @article{info:hdl:2013/311546b,
title = {Streaming active learning strategies for real-life credit card fraud detection: assessment and visualization},
author = {Fabrizio Carcillo and Yann-A"el Le Borgne and Olivier Caelen and Gianluca Bontempi},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/311546},
year = {2018},
date = {2018-01-01},
journal = {International journal of data science and analytics (Print)},
volume = {5},
number = {4},
pages = {285-300},
note = {DOI: 10.1007/s41060-018-0116-z},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Carcillo, Fabrizio; Borgne, Yann-A"el Le; Caelen, Olivier; Bontempi, Gianluca Correction to: Streaming active learning strategies for real-life credit detection: assessment and visualization Journal Article In: International journal of data science and analytics (Print), vol. 5, no. 4, pp. 301-302, 2018, (DOI: 10.1007/s41060-018-0123-0). @article{info:hdl:2013/311389b,
title = {Correction to: Streaming active learning strategies for real-life credit detection: assessment and visualization},
author = {Fabrizio Carcillo and Yann-A"el Le Borgne and Olivier Caelen and Gianluca Bontempi},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/311389},
year = {2018},
date = {2018-01-01},
journal = {International journal of data science and analytics (Print)},
volume = {5},
number = {4},
pages = {301-302},
note = {DOI: 10.1007/s41060-018-0123-0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Ioannidis, J. P. A.; Bhattacharya, S.; Evers, J. L. H.; Veen, F. V. Der; Somigliana, E.; Barratt, C. L. R.; Bontempi, Gianluca; Baird, D. T.; Crosignani, P.; Devroey, P; Diedrich, Klaus; Farquharson, R. G.; Fraser, L. R.; Geraedts, Joep Pm M; Gianaroli, Luca; Vecchia, C. La; Magli, C.; Negri, E.; Sunde, A.; Tapanainen, J. S.; Tarlatzis, Basil; Steirteghem, A. V.; Veiga, A. Protect us from poor-quality medical research Journal Article In: Human reproduction, vol. 33, no. 5, pp. 770-776, 2018, (DOI: 10.1093/humrep/dey056). @article{info:hdl:2013/272828b,
title = {Protect us from poor-quality medical research},
author = {J. P. A. Ioannidis and S. Bhattacharya and J. L. H. Evers and F. V. Der Veen and E. Somigliana and C. L. R. Barratt and Gianluca Bontempi and D. T. Baird and P. Crosignani and P Devroey and Klaus Diedrich and R. G. Farquharson and L. R. Fraser and Joep Pm M Geraedts and Luca Gianaroli and C. La Vecchia and C. Magli and E. Negri and A. Sunde and J. S. Tapanainen and Basil Tarlatzis and A. V. Steirteghem and A. Veiga},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/272828},
year = {2018},
date = {2018-01-01},
journal = {Human reproduction},
volume = {33},
number = {5},
pages = {770-776},
note = {DOI: 10.1093/humrep/dey056},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Raimondi, Daniele; Orlando, Gabriele; Tabaro, Francesco; Lenaerts, Tom; Rooman, Marianne; Moreau, Yves; Vranken, Wim F Large-scale in-silico statistical mutagenesis analysis sheds light on the deleteriousness landscape of the human proteome. Journal Article In: Scientific reports, vol. 8, no. 1, pp. 16980, 2018, (DOI: 10.1038/s41598-018-34959-7). @article{info:hdl:2013/283645,
title = {Large-scale in-silico statistical mutagenesis analysis sheds light on the deleteriousness landscape of the human proteome.},
author = {Daniele Raimondi and Gabriele Orlando and Francesco Tabaro and Tom Lenaerts and Marianne Rooman and Yves Moreau and Wim F Vranken},
url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/283645/4/doi_267272.pdf},
year = {2018},
date = {2018-01-01},
journal = {Scientific reports},
volume = {8},
number = {1},
pages = {16980},
abstract = {Next generation sequencing technologies are providing increasing amounts of sequencing data, paving the way for improvements in clinical genetics and precision medicine. The interpretation of the observed genomic variants in the light of their phenotypic effects is thus emerging as a crucial task to solve in order to advance our understanding of how exomic variants affect proteins and how the proteins' functional changes affect human health. Since the experimental evaluation of the effects of every observed variant is unfeasible, Bioinformatics methods are being developed to address this challenge in-silico, by predicting the impact of millions of variants, thus providing insight into the deleteriousness landscape of entire proteomes. Here we show the feasibility of this approach by using the recently developed DEOGEN2 variant-effect predictor to perform the largest in-silico mutagenesis scan to date. We computed the deleteriousness score of 170 million variants over 15000 human proteins and we analysed the results, investigating how the predicted deleteriousness landscape of the proteins relates to known functionally and structurally relevant protein regions and biophysical properties. Moreover, we qualitatively validated our results by comparing them with two mutagenesis studies targeting two specific proteins, showing the consistency of DEOGEN2 predictions with respect to experimental data.},
note = {DOI: 10.1038/s41598-018-34959-7},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Next generation sequencing technologies are providing increasing amounts of sequencing data, paving the way for improvements in clinical genetics and precision medicine. The interpretation of the observed genomic variants in the light of their phenotypic effects is thus emerging as a crucial task to solve in order to advance our understanding of how exomic variants affect proteins and how the proteins' functional changes affect human health. Since the experimental evaluation of the effects of every observed variant is unfeasible, Bioinformatics methods are being developed to address this challenge in-silico, by predicting the impact of millions of variants, thus providing insight into the deleteriousness landscape of entire proteomes. Here we show the feasibility of this approach by using the recently developed DEOGEN2 variant-effect predictor to perform the largest in-silico mutagenesis scan to date. We computed the deleteriousness score of 170 million variants over 15000 human proteins and we analysed the results, investigating how the predicted deleteriousness landscape of the proteins relates to known functionally and structurally relevant protein regions and biophysical properties. Moreover, we qualitatively validated our results by comparing them with two mutagenesis studies targeting two specific proteins, showing the consistency of DEOGEN2 predictions with respect to experimental data. |
Skiba, Grażyna; Starzec, Mateusz; Byrski, Aleksander; Rycerz, Katarzyna; Kisiel-Dorohinicki, Marek; Turek, Wojciech; Krzywicki, Daniel; Lenaerts, Tom; Burguillo, Juan Carlos Flexible asynchronous simulation of iterated prisoner's dilemma based on actor model Journal Article In: Simulation modelling practice and theory, vol. 83, pp. 75-92, 2018, (DOI: 10.1016/j.simpat.2017.12.010). @article{info:hdl:2013/272556b,
title = {Flexible asynchronous simulation of iterated prisoner's dilemma based on actor model},
author = {Grażyna Skiba and Mateusz Starzec and Aleksander Byrski and Katarzyna Rycerz and Marek Kisiel-Dorohinicki and Wojciech Turek and Daniel Krzywicki and Tom Lenaerts and Juan Carlos Burguillo},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/272556},
year = {2018},
date = {2018-01-01},
journal = {Simulation modelling practice and theory},
volume = {83},
pages = {75-92},
note = {DOI: 10.1016/j.simpat.2017.12.010},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Skiba, Gra. zyna; Starzec, Mateusz; Byrski, Aleksander; Rycerz, Katarzyna; Kisiel-Dorohinicki, Marek; Turek, Wojciech; Krzywicki, Daniel; Lenaerts, Tom; Burguillo, Juan Carlos Flexible asynchronous simulation of iterated prisoner's dilemma based on actor model Journal Article In: Simulation modelling practice and theory, vol. 83, pp. 75-92, 2018, (DOI: 10.1016/j.simpat.2017.12.010). @article{info:hdl:2013/272556,
title = {Flexible asynchronous simulation of iterated prisoner's dilemma based on actor model},
author = {Gra{.z}yna Skiba and Mateusz Starzec and Aleksander Byrski and Katarzyna Rycerz and Marek Kisiel-Dorohinicki and Wojciech Turek and Daniel Krzywicki and Tom Lenaerts and Juan Carlos Burguillo},
url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/272556/1/Elsevier_256183.pdf},
year = {2018},
date = {2018-01-01},
journal = {Simulation modelling practice and theory},
volume = {83},
pages = {75-92},
abstract = {The wide range of applications of the Iterated prisoner's dilemma (IPD) game made it a popular subject of study for the research community. As a consequence, numerous experiments have been conducted by researchers along the last decades. However, topics related with scaling simulation leveraging existing HPC infrastructure in the field of IPD did not always play a relevant role in such experimental work. The main contribution of this paper is a new simulation framework, based on asynchronous communication and its implementation oriented to distributed environments. Such framework is based on the modern Akka actor platform, that supports concurrent, distributed and resilient message-driven simulations; which are exemplified over the IPD game as a case study. We also present several interesting results regarding the introduction of asynchrony into the IPD simulation in order to obtain an efficient framework, so the whole simulation becomes scalable when using HPC facilities. The influence of asynchrony on the algorithm itself is also discussed, and the results show that it does not hamper the simulation.},
note = {DOI: 10.1016/j.simpat.2017.12.010},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The wide range of applications of the Iterated prisoner's dilemma (IPD) game made it a popular subject of study for the research community. As a consequence, numerous experiments have been conducted by researchers along the last decades. However, topics related with scaling simulation leveraging existing HPC infrastructure in the field of IPD did not always play a relevant role in such experimental work. The main contribution of this paper is a new simulation framework, based on asynchronous communication and its implementation oriented to distributed environments. Such framework is based on the modern Akka actor platform, that supports concurrent, distributed and resilient message-driven simulations; which are exemplified over the IPD game as a case study. We also present several interesting results regarding the introduction of asynchrony into the IPD simulation in order to obtain an efficient framework, so the whole simulation becomes scalable when using HPC facilities. The influence of asynchrony on the algorithm itself is also discussed, and the results show that it does not hamper the simulation. |
Kieken, Fabien; Loth, Karine; Nuland, Nico N. A. J.; Tompa, Peter; Lenaerts, Tom Chemical shift assignments of the partially deuterated Fyn SH2–SH3 domain Journal Article In: Biomolecular N M R Assignments, vol. 12, no. 1, pp. 117-122, 2018, (DOI: 10.1007/s12104-017-9792-1). @article{info:hdl:2013/272541b,
title = {Chemical shift assignments of the partially deuterated Fyn SH2–SH3 domain},
author = {Fabien Kieken and Karine Loth and Nico N. A. J. Nuland and Peter Tompa and Tom Lenaerts},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/272541},
year = {2018},
date = {2018-01-01},
journal = {Biomolecular N M R Assignments},
volume = {12},
number = {1},
pages = {117-122},
note = {DOI: 10.1007/s12104-017-9792-1},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Kieken, Fabien; Loth, Karine; van Nuland, Nico N A J; Tompa, Peter; Lenaerts, Tom Chemical shift assignments of the partially deuterated Fyn SH2--SH3 domain Journal Article In: Biomolecular N M R Assignments, vol. 12, no. 1, pp. 117-122, 2018, (DOI: 10.1007/s12104-017-9792-1). @article{info:hdl:2013/272541,
title = {Chemical shift assignments of the partially deuterated Fyn SH2--SH3 domain},
author = {Fabien Kieken and Karine Loth and Nico N A J van Nuland and Peter Tompa and Tom Lenaerts},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/272541},
year = {2018},
date = {2018-01-01},
journal = {Biomolecular N M R Assignments},
volume = {12},
number = {1},
pages = {117-122},
abstract = {Src Homology 2 and 3 (SH2 and SH3) are two key protein interaction modules involved in regulating the activity of many proteins such as tyrosine kinases and phosphatases by respective recognition of phosphotyrosine and proline-rich regions. In the Src family kinases, the inactive state of the protein is the direct result of the interaction of the SH2 and the SH3 domain with intra-molecular regions, leading to a closed structure incompetent with substrate modification. Here, we report the 1H, 15N and 13C backbone- and side-chain chemical shift assignments of the partially deuterated Fyn SH3--SH2 domain and structural differences between tandem and single domains. The BMRB accession number is 27165.},
note = {DOI: 10.1007/s12104-017-9792-1},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Src Homology 2 and 3 (SH2 and SH3) are two key protein interaction modules involved in regulating the activity of many proteins such as tyrosine kinases and phosphatases by respective recognition of phosphotyrosine and proline-rich regions. In the Src family kinases, the inactive state of the protein is the direct result of the interaction of the SH2 and the SH3 domain with intra-molecular regions, leading to a closed structure incompetent with substrate modification. Here, we report the 1H, 15N and 13C backbone- and side-chain chemical shift assignments of the partially deuterated Fyn SH3--SH2 domain and structural differences between tandem and single domains. The BMRB accession number is 27165. |
Trepo, Eric; Goossens, Nicolas; Fujiwara, Naoto; Song, Won-Min; Colaprico, Antonio; Marot, Astrid; Spahr, Laurent; Demetter, Pieter; Sempoux, Christine; Im, Gene Y; Saldarriaga, Joan; Gustot, Thierry; Devi`ere, Jacques; Thung, Swan SN; Minsart, Charlotte; Serste, Thomas; Bontempi, Gianluca; Abdelrahman, Karim; Henrion, Jean; Degré, Delphine; Lucidi, Valerio; Rubbia-Brandt, Laura; Nair, Venugopalan D; Moreno, Christophe; Deltenre, Pierre; Hoshida, Yujin; Franchimont, Denis Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis Journal Article In: Gastroenterology, vol. 154, no. 4, pp. 965-975, 2018, (DOI: 10.1053/j.gastro.2017.10.048). @article{info:hdl:2013/269084b,
title = {Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis},
author = {Eric Trepo and Nicolas Goossens and Naoto Fujiwara and Won-Min Song and Antonio Colaprico and Astrid Marot and Laurent Spahr and Pieter Demetter and Christine Sempoux and Gene Y Im and Joan Saldarriaga and Thierry Gustot and Jacques Devi`ere and Swan SN Thung and Charlotte Minsart and Thomas Serste and Gianluca Bontempi and Karim Abdelrahman and Jean Henrion and Delphine Degré and Valerio Lucidi and Laura Rubbia-Brandt and Venugopalan D Nair and Christophe Moreno and Pierre Deltenre and Yujin Hoshida and Denis Franchimont},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/269084},
year = {2018},
date = {2018-01-01},
journal = {Gastroenterology},
volume = {154},
number = {4},
pages = {965-975},
note = {DOI: 10.1053/j.gastro.2017.10.048},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Bontempi, Gianluca; Mauri, Giancarlo; Castiglioni, Isabella In-silico integration approach to identify a key miRNA regulating a gene network in aggressive prostate cancer Journal Article In: International journal of molecular sciences, vol. 19, no. 3, 2018, (DOI: 10.3390/ijms19030910). @article{info:hdl:2013/270452b,
title = {In-silico integration approach to identify a key miRNA regulating a gene network in aggressive prostate cancer},
author = {Claudia Cava and Gloria Bertoli and Antonio Colaprico and Gianluca Bontempi and Giancarlo Mauri and Isabella Castiglioni},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/270452},
year = {2018},
date = {2018-01-01},
journal = {International journal of molecular sciences},
volume = {19},
number = {3},
note = {DOI: 10.3390/ijms19030910},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Byrski, Aleksander; 'Swiderska, Ewelina; Łasisz, Jakub; Kisiel-Dorohinicki, Marek; Lenaerts, Tom; Samson, Dana; Indurkhya, Bipin Emergence of population structure in socio-cognitively inspired ant colony optimization Journal Article In: Computer Science, vol. 19, no. 1, pp. 81-98, 2018, (DOI: 10.7494/csci.2018.19.1.2594). @article{info:hdl:2013/270586,
title = {Emergence of population structure in socio-cognitively inspired ant colony optimization},
author = {Aleksander Byrski and Ewelina {'S}widerska and Jakub {Ł}asisz and Marek Kisiel-Dorohinicki and Tom Lenaerts and Dana Samson and Bipin Indurkhya},
url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/270586/1/doi_254213.pdf},
year = {2018},
date = {2018-01-01},
journal = {Computer Science},
volume = {19},
number = {1},
pages = {81-98},
abstract = {A metaheuristic proposed by us recently, Ant Colony Optimization (ACO) hybridized with socio-cognitive inspirations, turned out to generate interesting results when compared to classic ACO. Even though it does not always find better solutions to the considered problems, it usually finds sub-optimal solutions. Moreover, instead of a trial-and-error approach to configure the parameters of the ant species in the population, the actual structure of the population emerges from a predefined species-to-species ant migration strategies in our approach. Experimental results of our approach are compared to classic ACO and selected socio-cognitive versions of this algorithm.},
note = {DOI: 10.7494/csci.2018.19.1.2594},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A metaheuristic proposed by us recently, Ant Colony Optimization (ACO) hybridized with socio-cognitive inspirations, turned out to generate interesting results when compared to classic ACO. Even though it does not always find better solutions to the considered problems, it usually finds sub-optimal solutions. Moreover, instead of a trial-and-error approach to configure the parameters of the ant species in the population, the actual structure of the population emerges from a predefined species-to-species ant migration strategies in our approach. Experimental results of our approach are compared to classic ACO and selected socio-cognitive versions of this algorithm. |
Serroukh, Yasmina; Gu-Trantien, Chunyan; Kashani, Baharak Hooshiar; Defrance, Matthieu; Manh, Thien-Phong Vu; Azouz, Abdulkader; Detavernier, Aurélie; Hoyois, Alice; Das, Jishnu; Bizet, Martin; Pollet, Emeline; Tabbuso, Tressy; Calonne, Emilie; Gisbergen, Klaas; Dalod, Marc; Fuks, Franccois; Goriely, Stanislas; Marchant, Arnaud The transcription factors Runx3 and ThPOK cross-regulate acquisition of cytotoxic function by human Th1 lymphocytes. Journal Article In: eLife, vol. 7, 2018, (DOI: 10.7554/eLife.30496). @article{info:hdl:2013/268207b,
title = {The transcription factors Runx3 and ThPOK cross-regulate acquisition of cytotoxic function by human Th1 lymphocytes.},
author = {Yasmina Serroukh and Chunyan Gu-Trantien and Baharak Hooshiar Kashani and Matthieu Defrance and Thien-Phong Vu Manh and Abdulkader Azouz and Aurélie Detavernier and Alice Hoyois and Jishnu Das and Martin Bizet and Emeline Pollet and Tressy Tabbuso and Emilie Calonne and Klaas Gisbergen and Marc Dalod and Franccois Fuks and Stanislas Goriely and Arnaud Marchant},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/268207},
year = {2018},
date = {2018-01-01},
journal = {eLife},
volume = {7},
note = {DOI: 10.7554/eLife.30496},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
P`ere, Nathaniel Mon; Lenaerts, Tom; Pacheco, Jorge J M; Dingli, David Evolutionary Dynamics of Paroxysmal Nocturnal Hemoglobinuria Journal Article In: PLoS computational biology, vol. 14, no. 6, 2018, (DOI: 10.1371/journal.pcbi.1006133). @article{info:hdl:2013/267360,
title = {Evolutionary Dynamics of Paroxysmal Nocturnal Hemoglobinuria},
author = {Nathaniel Mon P{`e}re and Tom Lenaerts and Jorge J M Pacheco and David Dingli},
url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/267360/4/doi_250987.pdf},
year = {2018},
date = {2018-01-01},
journal = {PLoS computational biology},
volume = {14},
number = {6},
abstract = {Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal blood disorder characterized by hemolysis and a high risk of thrombosis, that is due to a deficiency in several cell surface proteins that prevent complement activation. Its origin has been traced to a somatic mutation in the PIG-A gene within hematopoietic stem cells (HSC). However, to date the question of how this mutant clone expands in size to contribute significantly to hematopoiesis remains under debate. One hypothesis posits the existence of a selective advantage of PIG-A mutated cells due to an immune mediated attack on normal HSC, but the evidence supporting this hypothesis is inconclusive. An alternative (and simpler) explanation attributes clonal expansion to neutral drift, in which case selection neither favours nor inhibits expansion of PIG-A mutated HSC. Here we examine the implications of the neutral drift model by numerically evolving a Markov chain for the probabilities of all possible outcomes, and investigate the possible occurrence and evolution, within this framework, of multiple independently arising clones within the HSC pool. Predictions of the model agree well with the known incidence of the disease and average age at diagnosis. Notwithstanding the slight difference in clonal expansion rates between our results and those reported in the literature, our model results lead to a relative stability of clone size when averaging multiple cases, in accord with what has been observed in human trials. The probability of a patient harbouring a second clone in the HSC pool was found to be extremely low (~10-8). Thus our results suggest that in clinical cases of PNH where two independent clones of mutant cells are observed, only one of those is likely to have originated in the HSC pool.},
note = {DOI: 10.1371/journal.pcbi.1006133},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal blood disorder characterized by hemolysis and a high risk of thrombosis, that is due to a deficiency in several cell surface proteins that prevent complement activation. Its origin has been traced to a somatic mutation in the PIG-A gene within hematopoietic stem cells (HSC). However, to date the question of how this mutant clone expands in size to contribute significantly to hematopoiesis remains under debate. One hypothesis posits the existence of a selective advantage of PIG-A mutated cells due to an immune mediated attack on normal HSC, but the evidence supporting this hypothesis is inconclusive. An alternative (and simpler) explanation attributes clonal expansion to neutral drift, in which case selection neither favours nor inhibits expansion of PIG-A mutated HSC. Here we examine the implications of the neutral drift model by numerically evolving a Markov chain for the probabilities of all possible outcomes, and investigate the possible occurrence and evolution, within this framework, of multiple independently arising clones within the HSC pool. Predictions of the model agree well with the known incidence of the disease and average age at diagnosis. Notwithstanding the slight difference in clonal expansion rates between our results and those reported in the literature, our model results lead to a relative stability of clone size when averaging multiple cases, in accord with what has been observed in human trials. The probability of a patient harbouring a second clone in the HSC pool was found to be extremely low (~10-8). Thus our results suggest that in clinical cases of PNH where two independent clones of mutant cells are observed, only one of those is likely to have originated in the HSC pool. |
Bogeas, Alexandra; Morvan-Dubois, Ghislaine; El-Habr, Elias E. A.; Lejeune, Franccois Xavier; Defrance, Matthieu; Narayanan, Ashwin; Kuranda, Klaudia; Burel-Vandenbos, Fanny; Sayd, Salwa; Delaunay, Virgile; Dubois, Luiz Gustavo Feijó L. G.; Parrinello, Hugues; Rialle, Stéphanie; Fabrega, Sylvie; Idbaih, Ahmed; Haiech, Jacques; Bieche, Ivan; Virolle, Thierry; Goodhardt, Michele; Chneiweiss, Hervé; Junier, Marie Pierre Changes in chromatin state reveal ARNT2 at a node of a tumorigenic transcription factor signature driving glioblastoma cell aggressiveness Journal Article In: Acta Neuropathologica, vol. 135, no. 2, pp. 267-283, 2018, (DOI: 10.1007/s00401-017-1783-x). @article{info:hdl:2013/272529b,
title = {Changes in chromatin state reveal ARNT2 at a node of a tumorigenic transcription factor signature driving glioblastoma cell aggressiveness},
author = {Alexandra Bogeas and Ghislaine Morvan-Dubois and Elias E. A. El-Habr and Franccois Xavier Lejeune and Matthieu Defrance and Ashwin Narayanan and Klaudia Kuranda and Fanny Burel-Vandenbos and Salwa Sayd and Virgile Delaunay and Luiz Gustavo Feijó L. G. Dubois and Hugues Parrinello and Stéphanie Rialle and Sylvie Fabrega and Ahmed Idbaih and Jacques Haiech and Ivan Bieche and Thierry Virolle and Michele Goodhardt and Hervé Chneiweiss and Marie Pierre Junier},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/272529},
year = {2018},
date = {2018-01-01},
journal = {Acta Neuropathologica},
volume = {135},
number = {2},
pages = {267-283},
note = {DOI: 10.1007/s00401-017-1783-x},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
P`ere, Nathaniel Mon; Lenaerts, Tom; Pacheco, Jorge J. M.; Dingli, David Evolutionary Dynamics of Paroxysmal Nocturnal Hemoglobinuria Journal Article In: PLoS computational biology, vol. 14, no. 6, 2018, (DOI: 10.1371/journal.pcbi.1006133). @article{info:hdl:2013/267360b,
title = {Evolutionary Dynamics of Paroxysmal Nocturnal Hemoglobinuria},
author = {Nathaniel Mon P`ere and Tom Lenaerts and Jorge J. M. Pacheco and David Dingli},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/267360},
year = {2018},
date = {2018-01-01},
journal = {PLoS computational biology},
volume = {14},
number = {6},
note = {DOI: 10.1371/journal.pcbi.1006133},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Byrski, Aleksander; Świderska, Ewelina; Łasisz, Jakub; Kisiel-Dorohinicki, Marek; Lenaerts, Tom; Samson, Dana; Indurkhya, Bipin Emergence of population structure in socio-cognitively inspired ant colony optimization Journal Article In: Computer Science, vol. 19, no. 1, pp. 81-98, 2018, (DOI: 10.7494/csci.2018.19.1.2594). @article{info:hdl:2013/270586b,
title = {Emergence of population structure in socio-cognitively inspired ant colony optimization},
author = {Aleksander Byrski and Ewelina Świderska and Jakub Łasisz and Marek Kisiel-Dorohinicki and Tom Lenaerts and Dana Samson and Bipin Indurkhya},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/270586},
year = {2018},
date = {2018-01-01},
journal = {Computer Science},
volume = {19},
number = {1},
pages = {81-98},
note = {DOI: 10.7494/csci.2018.19.1.2594},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Saykali, Bechara; Nahaboo, Wallis; Mathiah, Navrita; Racu, Marie-Lucie; Defrance, Matthieu; Migeotte, Isabelle Distinct mesoderm migration phenotypes in extra-embryonic and embryonic regions of the early mouse embryo Journal Article In: BioRxiv, 2018, (Language of publication: en). @article{info:hdl:2013/282216b,
title = {Distinct mesoderm migration phenotypes in extra-embryonic and embryonic regions of the early mouse embryo},
author = {Bechara Saykali and Wallis Nahaboo and Navrita Mathiah and Marie-Lucie Racu and Matthieu Defrance and Isabelle Migeotte},
url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/282216},
year = {2018},
date = {2018-01-01},
journal = {BioRxiv},
note = {Language of publication: en},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|