World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
73
Citations
22861
World Ranking
1580
National Ranking
824

Overview

Jean-Philippe Vert is affiliated with Google in the United States and has contributed extensively to the fields of biochemistry, genetics, and molecular biology. Their research addresses multiple subfields including molecular biology, artificial intelligence, biophysics, cancer research, and genetics.

Their recent publications demonstrate a focus on single-cell analysis, gene regulation, and applications of AI in biotechnology. Notable recent papers include:

  • Transcriptional Programs Define Intratumoral Heterogeneity of Ewing Sarcoma at Single-Cell Resolution, 2020, Cell Reports
  • DeepConsensus improves the accuracy of sequences with a gap-aware sequence transformer, 2022, Nature Biotechnology
  • Gene regulation inference from single-cell RNA-seq data with linear differential equations and velocity inference, 2020, Bioinformatics
  • AI-based mobile application to fight antibiotic resistance, 2021, Nature Communications
  • How will generative AI disrupt data science in drug discovery?, 2023, Nature Biotechnology

The main research topics in Jean-Philippe Vert's work include:

  • Single-cell and spatial transcriptomics
  • Cell image analysis techniques
  • RNA and protein synthesis mechanisms
  • Genomics and chromatin dynamics
  • Genomics and phylogenetic studies
  • Gene regulatory network analysis
  • Gene expression and cancer classification

Jean-Philippe Vert frequently publishes in the following venues:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Bioinformatics
  • Genome Biology

Frequent collaborators in their publications include:

  • William Stafford Noble
  • Félix Raimundo
  • Céline Vallot
  • Ran Zhang
  • Quentin Berthet

Jean-Philippe Vert's research integrates advanced computational techniques with molecular and cellular biological data. Their work often applies artificial intelligence tools to explore complex biological systems, gene regulation, and cancer heterogeneity at the single-cell level. This blend of disciplines reflects a commitment to developing new analytical frameworks for understanding molecular and genetic mechanisms in health and disease.

Best Publications

  • HiC-Pro: an optimized and flexible pipeline for Hi-C data processing

    Nicolas Servant;Nelle Varoquaux;Nelle Varoquaux;Nelle Varoquaux;Bryan R. Lajoie;Eric Viara

  • Group lasso with overlap and graph lasso

    Laurent Jacob;Guillaume Obozinski;Jean-Philippe Vert

  • Kernel Methods in Computational Biology

    Bernhard Schölkopf;Koji Tsuda;Jean-Philippe Vert

  • A general and flexible method for signal extraction from single-cell RNA-seq data

    Davide Risso;Fanny Perraudeau;Svetlana Gribkova;Sandrine Dudoit

  • Protein-ligand interaction prediction

    Laurent Jacob;Jean-Philippe Vert

  • Protein homology detection using string alignment kernels

    Hiroto Saigo;Jean-Philippe Vert;Nobuhisa Ueda;Tatsuya Akutsu

  • Clustered Multi-Task Learning: A Convex Formulation

    Laurent Jacob;Jean-philippe Vert;Francis R. Bach

  • TIGRESS: Trustful Inference of Gene REgulation using Stability Selection

    Anne-Claire Haury;Fantine Mordelet;Paola Vera-Licona;Paola Vera-Licona;Paola Vera-Licona;Jean-Philippe Vert;Jean-Philippe Vert;Jean-Philippe Vert

  • The Influence of Feature Selection Methods on Accuracy, Stability and Interpretability of Molecular Signatures

    Anne-Claire Haury;Pierre Gestraud;Jean-Philippe Vert

  • A Path Following Algorithm for the Graph Matching Problem

    M. Zaslavskiy;F. Bach;J.-P. Vert

  • A Primer on Kernel Methods

    JP Vert;K Tsuda;B Schölkopf;B. Schölkopf K. Tsuda

  • Support Vector Machine Applications in Computational Biology

    Bernhard Schölkopf;Koji Tsuda;Jean-Philippe Vert

  • An accurate and interpretable model for siRNA efficacy prediction

    Jean-Philippe Vert;Nicolas Foveau;Christian Lajaunie;Yves Vandenbrouck

  • Consistency of Random Forests

    Erwan Scornet;Gérard Biau;Jean-Philippe Vert

  • A bagging SVM to learn from positive and unlabeled examples

    F. Mordelet;J. P. Vert;J. P. Vert;J. P. Vert

  • Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization

    Valentina Boeva;Andrei Zinovyev;Kevin Bleakley;Jean-Philippe Vert

  • Classification of microarray data using gene networks

    Franck Rapaport;Franck Rapaport;Andrei Yu. Zinovyev;Marie Dutreix;Emmanuel Barillot

  • Protein network inference from multiple genomic data: a supervised approach

    Y. Yamanishi;J.-P. Vert;M. Kanehisa

  • A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization

    Jacob Abernethy;Francis Bach;Theodoros Evgeniou;Jean-Philippe Vert

  • A statistical approach for inferring the 3D structure of the genome

    Nelle Varoquaux;Ferhat Ay;William Stafford Noble;Jean Philippe Vert

  • Supervised reconstruction of biological networks with local models

    Kevin Bleakley;Gérard Biau;Jean-Philippe Vert

Frequent Co-Authors

Francis Bach
Francis Bach École Normale Supérieure
William Stafford Noble
William Stafford Noble University of Washington
Koji Tsuda
Koji Tsuda University of Tokyo
Marco Cuturi
Marco Cuturi École Nationale de la Statistique et de l'Administration Économique
Emmanuel Barillot
Emmanuel Barillot Institute Curie
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Andrei Zinovyev
Andrei Zinovyev Institute Curie
Tatsuya Akutsu
Tatsuya Akutsu Kyoto University
Ferhat Ay
Ferhat Ay La Jolla Institute For Allergy & Immunology
Minoru Kanehisa
Minoru Kanehisa Kyoto University

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