The joint IGMM/LIRMM/IMAG “Computational Regulatory Genomics” develops machine learning and statistical methods to integrate and interpret diverse types of genomics data, delineate relevant genomic regions and identify novel regulatory elements, with the ultimate goal of uncovering genetic features relevant to medical genomics.
More specifically, many loci can be transcribed outside annotated protein-coding gene promoters to generate various RNAs, e.g. enhancer RNAs, microRNAs and various long non-coding RNAs. On the other hand, genome-wide association studies show that trait-associated loci, including those linked to human diseases, can be found outside canonical protein-coding regions. These recent findings suggest that the non-coding regions of the human genome harbor a plethora of functionally significant elements, which can dramatically impact genome regulations and functions but yet remain to be explored. Their study is at the core of Computational Regulatory Genomics” team’s project.
This team was created in October 2014 at the Computational Biology Institute of Montpellier (http://www.ibc-montpellier.fr) and works in a highly interdisciplinary environment at the interface of computer science, statistics and biology. The members of the group have different backgrounds and are affiliated to the Institute of Molecular Genetics of Montpellier (IGMM; biology; http://www.igmm.cnrs.fr), the Laboratory of Informatics, Robotics and Microelectronics of Montpellier (LIRMM; computer science; http://www.lirmm.fr/recherche) and the Montpellier Alexander Grothendieck Institute (IMAG, statistics; http://imag.edu.umontpellier.fr).
Moreover, the team is engaged in several international collaborative research programs, notably through a CNRS International Associated Laboratory (1) with Pr. Wyeth W. Wasserman, University of British Columbia, Vancouver, Canada; https://cmmt.ubc.ca/wasserman-lab/) and the FANTOM consortium (2)(based at RIKEN Yokohama, Japan; http://fantom.gsc.riken.jp).
Regulatory genomics, transcription, medical genomics, bioinformatics, statistics, machine learning.
Laurent Bréhélin, CNRS Researcher, LIRMM
Sophie Lèbre, Associate Professor, IMAG & University of Montpellier
Charles-Henri Lecellier, CNRS Researcher, IGMM
Chloé Bessière, Research Engineer, IGMM
Christophe Menichelli, PhD sSudent, LIRMM
Raphael Romero, PhD Student, IMAG
Oceane Cassan, Master Student from ENSA Lyon
Mathys Grapotte, Master Student, from University of Montpellier & Télécom St Etienne
Previous lab members
Amadou Kide Abdallahi, Master Student, from University Paris 7
Florent Petitprez, Master Student from Ecole Polytechnique
Manu Saraswat, Master Student from BiTS Pilani Goa
May Taha, PhD Student from IGMM & IMAG
Jimmy Vandel, Post-Doc