Team
CBIO
Biography
Vincent Mallet is a researcher whose work focuses on the development of computational tools applied to structural and molecular biology. His research primarily focuses on the analysis of protein-protein interactions (PPIs) and the three-dimensional structures of RNAs and proteins, incorporating advanced methods of machine learning and molecular modeling. He has contributed to innovative approaches for predicting functional binding sites, notably through platforms such as InDeepNet, which combine deep learning with the assessment of the ligand-binding potential of protein conformations. His work on RNAs includes the development of pipelines for virtual structural screening, as well as tools such as RNAglib and VeRNAl, aimed at leveraging graphical representations of non-canonical interactions to better understand structure-function relationships. In addition, he has developed methodologies for analyzing big data, such as AlignScape—based on self-organizing maps—which enables the effective visualization and classification of protein families.
Publication(s)
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2025
InDeepNet: A web platform for predicting functional binding sites in proteins using InDeep DOI : 10.1093/nar/gkaf403
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2025
3D-Based RNA Function Prediction Tools in rnaglib DOI : 10.1007/978-1-0716-4079-1_10
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2025
Finding antibodies in cryo-EM maps with CrAI DOI : 10.1093/bioinformatics/btaf157
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2025
RNAmigos2: accelerated structure-based RNA virtual screening with deep graph learning DOI : 10.1038/s41467-025-57852-0
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2025
ATOMSURF: SURFACE REPRESENTATION FOR LEARNING ON PROTEIN STRUCTURES
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2024
AlignScape, displaying sequence similarity using self-organizing maps DOI : 10.3389/fbinf.2024.1321508
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2022
InDeep: 3D fully convolutional neural networks to assist in silico drug design on protein-protein interactions DOI : 10.1093/bioinformatics/btab849
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2022
RNAglib: A python package for RNA 2.5 D graphs DOI : 10.1093/bioinformatics/btab844
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2022
VeRNAl: a tool for mining fuzzy network motifs in RNA DOI : 10.1093/bioinformatics/btab768
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2021
Quicksom: Self-Organizing Maps on GPUs for clustering of molecular dynamics trajectories DOI : 10.1093/bioinformatics/btaa925
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2021
Reverse-Complement Equivariant Networks for DNA Sequences
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2020
OptiMol: Optimization of Binding Affinities in Chemical Space for Drug Discovery DOI : 10.1021/acs.jcim.0c00833
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2020
Augmented base pairing networks encode RNA-small molecule binding preferences DOI : 10.1093/nar/gkaa583
PhD supervision
- 2025 Multimodal representations of protein structures oriented towards interaction prediction GERTNER Victor
- 2024 Systems biology and machine learning approaches for identifying therapeutic targets and their associated drugs. Application to the identification of new therapeutic strategies for cystic fibrosis. LAIGLE Victor
- 2024 RNA encoding by machine learning for drug discovery KARROUCHA Wissam