Raphaël Mourad

18 papers Journal 13Unranked 3
YearRankTypeTitle / Venue / Authors
2024 J jnl
Semi-supervised learning with pseudo-labeling compares favorably with large language models for regulatory sequence prediction.
Briefings Bioinform.
Han Phan, Céline Brouard, Raphaël Mourad
2024 J jnl
Should we really use graph neural networks for transcriptomic prediction?
Briefings Bioinform.
Céline Brouard, Raphaël Mourad, Nathalie Vialaneix
2023 J jnl
Semi-supervised learning improves regulatory sequence prediction with unlabeled sequences.
BMC Bioinform.
Raphaël Mourad
2022 — book
Data analyses and bioinformatic models for genomics. (Analyses de données et modèles bioinformatiques pour la génomique).
Raphaël Mourad
2022 J jnl
TADreg: a versatile regression framework for TAD identification, differential analysis and rearranged 3D genome prediction.
BMC Bioinform.
Raphaël Mourad
2021 J jnl
DeepG4: A deep learning approach to predict cell-type specific active G-quadruplex regions.
PLoS Comput. Biol.
Vincent Rocher, Matthieu Genais, Elissar Nassereddine, Raphaël Mourad
2020 J jnl
Studying 3D genome evolution using genomic sequence.
Bioinform.
Raphaël Mourad
2017 J jnl
Uncovering direct and indirect molecular determinants of chromatin loops using a computational integrative approach.
PLoS Comput. Biol.
Raphaël Mourad, Lang Li, Olivier Cuvier
2016 J jnl
Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation.
PLoS Comput. Biol.
Raphaël Mourad, Olivier Cuvier
2014 J jnl
A Survey on Latent Tree Models and Applications.
CoRR
Raphaël Mourad, Christine Sinoquet, Nevin Lianwen Zhang, Tengfei Liu, Philippe Leray
2013 J jnl
A Survey on Latent Tree Models and Applications.
J. Artif. Intell. Res.
Raphaël Mourad, Christine Sinoquet, Nevin Lianwen Zhang, Tengfei Liu, Philippe Leray
2012 J jnl
A dynamic time order network for time-series gene expression data analysis.
BMC Syst. Biol.
Pengyue Zhang, Raphaël Mourad, Yang Xiang, Kun Huang, Tim Hui-Ming Huang, Kenneth P. Nephew, Yunlong Liu, Lang Li
2012 — conf
Forests of Latent Tree Models for the Detection of Genetic Associations.
BIOINFORMATICS
Christine Sinoquet, Raphaël Mourad, Philippe Leray
2012 — conf
Forests of Latent Tree Models to Decipher Genotype-Phenotype Associations.
BIOSTEC (Selected Papers)
Christine Sinoquet, Raphaël Mourad, Philippe Leray
2012 J jnl
Probabilistic graphical models for genetic association studies.
Briefings Bioinform.
Raphaël Mourad, Christine Sinoquet, Philippe Leray
2011 J jnl
A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-wide association studies.
BMC Bioinform.
Raphaël Mourad, Christine Sinoquet, Philippe Leray
2011 — —
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).
Raphaël Mourad
2010 — conf
Learning Hierarchical Bayesian Networks for Genome-Wide Association Studies.
COMPSTAT
Raphaël Mourad, Christine Sinoquet, Philippe Leray