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Raphaël Mourad
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2020 – today
- 2024
- [j11]Céline Brouard, Raphaël Mourad, Nathalie Vialaneix:
Should we really use graph neural networks for transcriptomic prediction? Briefings Bioinform. 25(2) (2024) - 2023
- [j10]Raphaël Mourad:
Semi-supervised learning improves regulatory sequence prediction with unlabeled sequences. BMC Bioinform. 24(1): 186 (2023) - 2022
- [b2]Raphaël Mourad:
Data analyses and bioinformatic models for genomics. (Analyses de données et modèles bioinformatiques pour la génomique). Paul Sabatier University, Toulouse, France, 2022 - [j9]Raphaël Mourad:
TADreg: a versatile regression framework for TAD identification, differential analysis and rearranged 3D genome prediction. BMC Bioinform. 23(1): 82 (2022) - 2021
- [j8]Vincent Rocher, Matthieu Genais, Elissar Nassereddine, Raphaël Mourad:
DeepG4: A deep learning approach to predict cell-type specific active G-quadruplex regions. PLoS Comput. Biol. 17(8) (2021) - 2020
- [j7]Raphaël Mourad:
Studying 3D genome evolution using genomic sequence. Bioinform. 36(5): 1367-1373 (2020)
2010 – 2019
- 2017
- [j6]Raphaël Mourad, Lang Li, Olivier Cuvier:
Uncovering direct and indirect molecular determinants of chromatin loops using a computational integrative approach. PLoS Comput. Biol. 13(5) (2017) - 2016
- [j5]Raphaël Mourad, Olivier Cuvier:
Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation. PLoS Comput. Biol. 12(5) (2016) - 2014
- [i1]Raphaël Mourad, Christine Sinoquet, Nevin Lianwen Zhang, Tengfei Liu, Philippe Leray:
A Survey on Latent Tree Models and Applications. CoRR abs/1402.0577 (2014) - 2013
- [j4]Raphaël Mourad, Christine Sinoquet, Nevin Lianwen Zhang, Tengfei Liu, Philippe Leray:
A Survey on Latent Tree Models and Applications. J. Artif. Intell. Res. 47: 157-203 (2013) - 2012
- [j3]Raphaël Mourad, Christine Sinoquet, Philippe Leray:
Probabilistic graphical models for genetic association studies. Briefings Bioinform. 13(1): 20-33 (2012) - [j2]Pengyue Zhang, Raphaël Mourad, Yang Xiang, Kun Huang, Tim Hui-Ming Huang, Kenneth P. Nephew, Yunlong Liu, Lang Li:
A dynamic time order network for time-series gene expression data analysis. BMC Syst. Biol. 6(S-3): S9 (2012) - [c3]Christine Sinoquet, Raphaël Mourad, Philippe Leray:
Forests of Latent Tree Models for the Detection of Genetic Associations. BIOINFORMATICS 2012: 5-14 - [c2]Christine Sinoquet, Raphaël Mourad, Philippe Leray:
Forests of Latent Tree Models to Decipher Genotype-Phenotype Associations. BIOSTEC (Selected Papers) 2012: 113-134 - 2011
- [b1]Raphaël Mourad:
Modélisation pangénomique du déséquilibre de liaison à l'aide de réseaux bayésiens hiérarchiques latents et applications. (Genome-wide linkage disequilibrium modeling using hierarchical latent Bayesian networks and applications). University of Nantes, France, 2011 - [j1]Raphaël Mourad, Christine Sinoquet, Philippe Leray:
A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-wide association studies. BMC Bioinform. 12: 16 (2011) - 2010
- [c1]Raphaël Mourad, Christine Sinoquet, Philippe Leray:
Learning Hierarchical Bayesian Networks for Genome-Wide Association Studies. COMPSTAT 2010: 549-556
Coauthor Index
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