Amibio (LIX, Ecole Polytechnique) is a research group in computational biology with a primary interest on the molecular levels of organization in the cell, and a strong focus on RNAs. Starting from the genomic sequences and NGS data, we currently concentrate our efforts on structures, interactions, evolution and design, trying to meet the growing needs for a rational synthetic biology. Towards that goal, we develop methodological approaches, based on abstract models that are computationally tractable and biologically relevant. A common toolkit of computational methods is developed, relying on our strong background in discrete mathematics, algorithmic design and analysis. Our ultimate goal is to provide software tools and platform elements, to formulate and test hypotheses for the sequence/structure/function relationship in molecular biology.
Research
Our team addresses central questions in bioninformatics, related to the molecular levels of organization in the cells. The biological function of macromolecules such as proteins and nucleic acids relies on their dynamic structural nature and their ability to interact with many different partners. Therefore, folding and docking are still major issues in modern structural biology and we currently concentrate our efforts on structure and interactions and aim at a contribution to RNA design. With the recent development of computational methods aiming to integrate different levels of information, protein and nucleic acid assemblies studies should provide a better understanding on the molecular processes and machinery occurring in the cell and our research extends to several related issues in comparative genomics.
On the one hand, we study and develop methodological approaches for dealing with macromolecular structures and annotation: the challenge is to develop abstract models that are computationally tractable and biologically relevant. Our approach puts a strong emphasis on the modeling of biological objects using classic formalisms in computer science (languages, trees, graphs…), occasionally decorated and/or weighted to capture features of interest. To that purpose, we rely on the wide array of skills present in our team in the fields of combinatorics, formal languages and discrete mathematics. The resulting models are usually designed to be amenable to a probabilistic analysis, which can be used to assess the relevance of models, or test general hypotheses.
On the other hand, once suitable models are established we apply these computational approaches to several particular problems arising in fundamental molecular biology. One typically aims at designing new specialized algorithms and methods to efficiently compute properties of real biological objects. Tools of choice include exact optimization, relying heavily on dynamic programming, simulations, machine learning and discrete mathematics. As a whole, a common toolkit of computational methods is developed within the group.The trade-off between the biological accuracy of the model and the computational tractability or efficiency is to be addressed in a close partnership with experimental biology groups. One outcome is to provide software or platform elements to predict structural models and functional hypotheses.
Members
Faculty members

CNRS Researcher (DR)

Full Prof. at Ecole Polytechnique

Asst Prof. at Ecole Polytechnique

Full Prof. (aemeritus) at Ecole Polytechnique
Administrative Assistant
Hélène Thibault – CNRS administrator
PhD Students

Taher Yacoub
Co-supervised with Fabrice Leclerc (I2BC@Univ. Paris Saclay)

Co-supervised with Laurent Bulteau (CNRS/LIGM)
Alumni
Former faculty members and staff

Inria Research Director (DR) – AMIBio founder and former lead (2009/16)
Now director of Inria Lille Nord-Europe research center

Prof. at Ecole Polytechnique

Evelyne Rayssac
Former AMIBio administrator
Ecole Polytechnique
Julie Bernauer – Former Inria Researcher (CR) – Now at nVidia, USA
Former postdoctoral fellows
- Olga Berillo – Research associate@ Lady Davis Institute, Canada
- Rasmus Fonseca – R&D developper@zoox.com
- Loic Paulevé – CNRS Researcher@LABRI, Bordeaux
- Balaji Raman – Associate professor@IIIT Sri City, India
- Christelle Rovetta – Data Scientist@Fujitsu France
- Saad Sheikh – Tech lead@Facebook, USA
Former PhD candidates

Hua-Ting Yao
PhD 2021 (Polytechnique + Univ. McGill)
Now postdoc at Univ. of Vienna, Austria

Ha Ngoc Nguyen
PhD 2020 (Univ. Paris Saclay)
Now Lecturer at Thuy Loi University, Vietnam

Jorgelindo Da Veiga Moreira
PhD 2019 (Polytechnique)
Now postdoc at Polytechnique Montreal, Canada

Juraj Michalik
PhD 2019 (Polytechnique)
Now postdoc at Czech Academy of Sciences, Czech Republic

Afaf Saaidi
PhD 2018 (Polytechnique)
Now postdoc at Georgia Tech, USA

Wei Wang
PhD 2017 (Univ Paris Saclay)
Now research at Merck Shanghai, China

Alice Héliou
PhD 2017 (Polytechnique)
Currently data scientist at Thalès, France

Amélie Héliou
PhD 2017 (Polytechnique)
Currently senior ML engineer at Criteo, France

Vladimir Reinharz
PhD 2016 (Univ Mc Gill, Canada)
Now Asst Prof at UQAM, Montreal, Canada
- Ievgeniia Furletova – Lecturer@IMPB, Russia
- Adrien Guilhot-Gaudeffroy – R&D@Thales
- Daria Iakovishina – CEO/founder@Ksivalue.com, Russia
- Vincent Le Gallic – R&D engineer@Telecom Paris Tech
- Pauline/Maria Pommeret
- Antoine Soulé – Postdoc@University McGill, Canada
Former visiting Scientists
- Cédric Chauve – Simon Fraser University, Canada
- Peter Clote – Boston College, USA
- Robert Giegerich – Univ. Bielefeld, Germany
- Vsevolod Makeev – Vavilov Institute of General Genetics, Russian Academy of Science
- Laurent Mouchard – University of Rouen
- Laurent Schwarz – APHP
Amibio (LIX, Ecole Polytechnique) is a research group in computational biology with a primary interest on the molecular levels of organization in the cell, and a strong focus on RNAs. Starting from the genomic sequences and NGS data, we currently concentrate our efforts on structures, interactions, evolution and design, trying to meet the growing needs for a rational synthetic biology. Towards that goal, we develop methodological approaches, based on abstract models that are computationally tractable and biologically relevant. A common toolkit of computational methods is developed, relying on our strong background in discrete mathematics, algorithmic design and analysis. Our ultimate goal is to provide software tools and platform elements, to formulate and test hypotheses for the sequence/structure/function relationship in molecular biology.