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1. Meet-U: Educating through research immersion.

Author

Nika Abdollahi, Alexandre Albani, Eric Anthony, Agnes Baud, Mélissa Cardon, Robert Clerc, Dariusz Czernecki, Romain Conte, Laurent David, Agathe Delaune, Samia Djerroud, Pauline Fourgoux, Nadège Guiglielmoni, Jeanne Laurentie, Nathalie Lehmann, Camille Lochard, Rémi Montagne, Vasiliki Myrodia, Vaitea Opuu, Elise Parey, Lélia Polit, Sylvain Privé, Chloé Quignot, Maria Ruiz-Cuevas, Mariam Sissoko, Nicolas Sompairac, Audrey Vallerix, Violaine Verrecchia, Marc Delarue, Raphael Guérois, Yann Ponty, Sophie Sacquin-Mora, Alessandra Carbone, Christine Froidevaux, Stéphane Le Crom, Olivier Lespinet, Martin Weigt, Samer Abboud, Juliana Bernardes, Guillaume Bouvier, Chloé Dequeker, Arnaud Ferré, Patrick Fuchs, Gaëlle Lelandais, Pierre Poulain, Hugues Richard, Hugo Schweke, Elodie Laine, and Anne Lopes

Subjects
Biology (General), QH301-705.5
Abstract

We present a new educational initiative called Meet-U that aims to train students for collaborative work in computational biology and to bridge the gap between education and research. Meet-U mimics the setup of collaborative research projects and takes advantage of the most popular tools for collaborative work and of cloud computing. Students are grouped in teams of 4-5 people and have to realize a project from A to Z that answers a challenging question in biology. Meet-U promotes "coopetition," as the students collaborate within and across the teams and are also in competition with each other to develop the best final product. Meet-U fosters interactions between different actors of education and research through the organization of a meeting day, open to everyone, where the students present their work to a jury of researchers and jury members give research seminars. This very unique combination of education and research is strongly motivating for the students and provides a formidable opportunity for a scientific community to unite and increase its visibility. We report on our experience with Meet-U in two French universities with master's students in bioinformatics and modeling, with protein-protein docking as the subject of the course. Meet-U is easy to implement and can be straightforwardly transferred to other fields and/or universities. All the information and data are available at www.meet-u.org.

Published
2018
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3. Discriminating physiological from non-physiological interfaces in structures of protein complexes: a community-wide study

Author

Hugo Schweke, Qifang Xu, Gerardo Tauriello, Lorenzo Pantolini, Torsten Schwede, Frédéric Cazals, Alix Lhéritier, Juan Fernandez-Recio, Luis Ángel Rodríguez-Lumbreras, Ora Schueler-Furman, Julia K. Varga, Brian Jiménez-García, Manon F. Réau, Alexandre Bonvin, Castrense Savojardo, Pier-Luigi Martelli, Rita Casadio, Jérôme Tubiana, Haim Wolfson, Romina Oliva, Didier Barradas-Bautista, Tiziana Ricciardelli, Luigi Cavallo, Česlovas Venclovas, Kliment Olechnovič, Raphael Guerois, Jessica Andreani, Juliette Martin, Xiao Wang, Daisuke Kihara, Anthony Marchand, Bruno Correia, Xiaoqin Zou, Sucharita Dey, Roland Dunbrack, Emmanuel Levy, and Shoshana Wodak

Abstract

Reliably scoring and ranking candidate models of protein complexes and assigning their oligomeric state from the structure of the crystal lattice represent outstanding challenges. A community-wide effort was launched to tackle these challenges. The latest resources on protein complexes and interfaces were exploited to derive a benchmark dataset consisting of 1677 homodimer protein crystal structures, including a balanced mix of physiological and non-physiological complexes. The non-physiological complexes in the benchmark were selected to bury a similar or larger interface area than their physiological counterparts, making it more difficult for scoring functions to differentiate between them. Next, 252 functions for scoring protein-protein interfaces previously developed by 13 groups were collected and evaluated for their ability to discriminate between physiological and non-physiological complexes. A simple consensus score generated using the best performing score of each of the 13 groups, and a cross-validated Random Forest (RF) classifier were created. Both approaches showed excellent performance, with an area under the Receiver Operating Characteristic (ROC) curve of 0.93 and 0.94 respectively, outperforming individual scores developed by different groups. Additionally, AlphaFold2 engines were shown to recall the physiological dimers with significantly higher accuracy than the non-physiological set, lending support for the pertinence of our benchmark dataset. Optimizing the combined power of interface scoring functions and evaluating it on challenging benchmark datasets appears to be a promising strategy.

Published
2023
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4. SURFMAP: a software for mapping in two dimensions protein surface features

Author

Nicolas Chevrollier, Marie-Hélène Mucchielli, Hugo Schweke, Simon Gosset, and Anne Lopes

Subjects
Computer science, business.industry, Protein Data Bank (RCSB PDB), Pattern recognition, Protein superfamily, Column (database), Software, Factor (programming language), Artificial intelligence, Representation (mathematics), business, Projection (set theory), Surface protein, computer, computer.programming_language
Abstract

Molecular cartography using two-dimensional (2D) representation of protein surfaces has been shown to be very promising for protein surface analysis. Here, we present SURFMAP, a free standalone and easy-to-use software that enables the fast and automated 2D projection of either predefined features of protein surface (i.e., electrostatic potential, Kyte-Doolittle hydrophobicity, stickiness, and surface relief) or any descriptor encoded in the temperature factor column of a PDB file. SURFMAP uses a pseudo-cylindrical sinusoidal “equal-area” projection that has the advantage of preserving the area measures. It provides the user with (i) 2D maps that enable the easy and visual analysis of protein surface features of interest and (ii) maps in a text file format allowing the fast and straightforward quantitative comparison of 2D maps of homologous proteins.

Published
2021
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5. Protein interaction energy landscapes are shaped by functional and also non-functional partners

Author

Anne Lopes, Hugo Schweke, Wanying Bei, Marie-Hélène Mucchielli, Sophie Sacquin-Mora, Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), BioInformatique Moléculaire (BIM), Département Biologie des Génomes (DBG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Laboratoire de biochimie théorique [Paris] (LBT (UPR_9080)), Institut de biologie physico-chimique (IBPC (FR_550)), and Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Molecular model, Protein family, Computer science, Protein Conformation, Non functional, [SDV]Life Sciences [q-bio], Computational biology, Protein–protein interaction, 03 medical and health sciences, 0302 clinical medicine, Sequence Analysis, Protein, Structural Biology, Protein Interaction Mapping, Humans, Macromolecular docking, Binding site, Databases, Protein, Molecular Biology, 030304 developmental biology, Physics, 0303 health sciences, A protein, Proteins, Interaction energy, Molecular Docking Simulation, Docking (molecular), Proteome, 030217 neurology & neurosurgery, Protein Binding
Abstract

International audience; In the crowded cell, a strong selective pressure operates on the proteome to limit the competition between functional and non-functional protein-protein interactions. We developed an original theoretical framework in order to interrogate how this competition constrains the behavior of proteins with respect to their partners or random encounters. Our theoretical framework relies on a two-dimensional (2D) representation of interaction energy landscapes with 2D energy maps that reflect in a synthetic way the propensity of a protein to interact with another protein. We investigated the propensity of protein surfaces to interact with functional and arbitrary partners and asked whether their interaction propensity is conserved during the evolution. Therefore, we performed several thousands of cross-docking simulations to systematically characterize the whole energy landscapes of 74 proteins interacting with different sets of homologs, corresponding to their functional partner’s family or arbitrary protein families. Then, we systematically compared the energy maps resulting from the docking of a given protein with the different protein families of the dataset. Strikingly, we show that the interaction propensity not only of the binding site but also of the rest of the protein surface is conserved for docking partners belonging to the same protein family. Interestingly, this observation holds for docked proteins corresponding to true but also to arbitrary partners. Our theoretical framework enables the characterization of the energy behavior of a protein in interaction with hundreds of selected partners and opens the way for further developments to study the behavior of proteins in a specific environment.; In the crowded cell, a strong selective pressure operates on the proteome to limit the competition between functional and non-functional protein-protein interactions. We developed an original theoretical framework in order to interrogate how this competition constrains the behavior of proteins with respect to their partners or random encounters. Our theoretical framework relies on a two-dimensional (2D) representation of interaction energy landscapes, with 2D energy maps, which reflect in a synthetic way the spatial distribution of the interaction propensity of a protein surface for another protein. We realized the interaction propensity mapping of proteins surfaces in interaction with functional and arbitrary partners and asked whether the distribution of their interaction propensity is conserved during evolution. Therefore, we performed several thousands of cross-docking simulations to systematically characterize the energy landscapes of 103 proteins interacting with different sets of homologs, corresponding to their functional partner's family or arbitrary protein families. Then, we systematically compared the energy maps resulting from the docking of each protein with the different protein families of the dataset. Strikingly, we show that the interaction propensity not only of the binding sites but also of the rest of the surface is conserved for docking partners belonging to the same protein family. Interestingly, this observation holds for docked proteins corresponding to true but also arbitrary partners. Our theoretical framework enables the characterization of the energy behavior of a protein in interaction with hundreds of proteins and opens the way for the characterization of the behavior of proteins in a specific environment.

Published
2020
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6. Meet-U: educating through research immersion

Author

Anne Lopes, Laurent David, Sophie Sacquin-Mora, Alexandre Albani, Marc Delarue, Vasiliki Myrodia, Eric Anthony, Mélissa Cardon, Hugo Schweke, Nicolas Sompairac, Stéphane Le Crom, Christine Froidevaux, Patrick F.J. Fuchs, Pierre Poulain, Violaine Verrecchia, Jeanne Laurentie, Nadège Guiglielmoni, Raphael Guerois, Martin Weigt, Maria Ruiz-Cuevas, Juliana S Bernardes, Samer Abboud, Rémi Montagne, Nathalie Lehmann, Vaitea Opuu, Chloé Quignot, Agnes Baud, Camille Lochard, Chloé Dequeker, Samia Djerroud, Romain Conte, Elodie Laine, Dariusz Czernecki, Olivier Lespinet, Mariam Sissoko, Agathe Delaune, Guillaume Bouvier, Arnaud Ferré, Audrey Vallerix, Robert Clerc, Hugues Richard, Alessandra Carbone, Elise Parey, Sylvain Privé, Pauline Fourgoux, Nika Abdollahi, Yann Ponty, Lélia Polit, Gaëlle Lelandais, Sorbonne Universités, Université Paris-Saclay, Dynamique structurale des Macromolécules / Structural Dynamics of Macromolecules, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Institut de Biologie Intégrative de la Cellule (I2BC), Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Assemblage moléculaire et intégrité du génome (AMIG), Département Biochimie, Biophysique et Biologie Structurale (B3S), Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Intégrative de la Cellule (I2BC), Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'informatique de l'École polytechnique [Palaiseau] (LIX), Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X), Algorithms and Models for Integrative BIOlogy (AMIBIO), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire de biochimie théorique [Paris] (LBT (UPR_9080)), Centre National de la Recherche Scientifique (CNRS)-Institut de biologie physico-chimique (IBPC), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7), Biologie Computationnelle et Quantitative = Laboratory of Computational and Quantitative Biology (LCQB), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Recherche en Informatique (LRI), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Bioinformatique structurale, Mathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] (MaIAGE), Institut National de la Recherche Agronomique (INRA), Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Biologie Intégrée du Globule Rouge (BIGR (UMR_S_1134 / U1134)), Institut National de la Transfusion Sanguine [Paris] (INTS)-Université Paris Diderot - Paris 7 (UPD7)-Université de La Réunion (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -Université des Antilles (UA)-Institut National de la Transfusion Sanguine [Paris] (INTS)-Université Paris Diderot - Paris 7 (UPD7)-Université de La Réunion (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -Université des Antilles (UA), Institut de biologie physico-chimique (IBPC), Centre National de la Recherche Scientifique (CNRS), Université Paris Diderot - Paris 7 (UPD7)-Institut de biologie physico-chimique (IBPC), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université des Antilles (UA)-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -Université de La Réunion (UR)-Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Transfusion Sanguine [Paris] (INTS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université des Antilles (UA)-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -Université de La Réunion (UR)-Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Transfusion Sanguine [Paris] (INTS), GenomiqueENS (Genomique ENS), Institut de biologie de l'ENS Paris (IBENS), Département de Biologie - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Département de Biologie - ENS Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Genetic Networks [LCQB] (LCQB-GN), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), Institut de biologie physico-chimique (IBPC (FR_550)), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Analyse des Données à Haut Débit en Génomique (ADHDG), Evolution Paris Seine, Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS), Bioinformatique structurale - Structural Bioinformatics, Institut National de la Transfusion Sanguine [Paris] (INTS)-Université Paris Diderot - Paris 7 (UPD7)-Université de La Réunion (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université des Antilles (UA)-Institut National de la Transfusion Sanguine [Paris] (INTS)-Université Paris Diderot - Paris 7 (UPD7)-Université de La Réunion (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université des Antilles (UA), Institut Jacques Monod (IJM (UMR_7592)), Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Masters of Computer Science and of Molecular and Cellular Biology at Sorbonne Université / UPMC (Bioinformatics and Modeling specialty), Master of Analysis, Modeling and Engineering of Biological and Medical Information at Université Paris-Saclay, Groupement de Recherche BioInformatique Moléculaire, Société Française de BioInformatique, Ecole Doctorale Structure et Dynamique des Systèmes Vivants, Institut de Biologie Paris Seine, Institut Universitaire de France, Biochimie Structurale, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique ( CNRS ), Institut de Biologie Intégrative de la Cellule ( I2BC ), Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Sud - Paris 11 ( UP11 ), Laboratoire d'informatique de l'École polytechnique [Palaiseau] ( LIX ), Centre National de la Recherche Scientifique ( CNRS ) -École polytechnique ( X ), Algorithms and Models for Integrative BIOlogy ( AMIBIO ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Laboratoire de biochimie théorique [Paris] ( LBT ), Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ), Biologie Computationnelle et Quantitative = Laboratory of Computational and Quantitative Biology ( LCQB ), Centre National de la Recherche Scientifique ( CNRS ) -Université Pierre et Marie Curie - Paris 6 ( UPMC ), Laboratoire de Recherche en Informatique ( LRI ), Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ), Institut de Biologie Paris Seine ( IBPS ), Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Centre National de la Recherche Scientifique ( CNRS ), Mathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] ( MaIAGE ), Institut National de la Recherche Agronomique ( INRA ), Dynamique des Structures et Interactions des Macromolécules Biologiques ( DSIMB ), Institut National de la Transfusion Sanguine [Paris] ( INTS ) -Université Paris Diderot - Paris 7 ( UPD7 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Institut de biologie physico-chimique ( IBPC ), Centre National de la Recherche Scientifique ( CNRS ), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Institut de biologie physico-chimique (IBPC (FR_550)), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC), CentraleSupélec-Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS), Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (... - 2019) (UNS), Université de Paris (UP)-Centre National de la Recherche Scientifique (CNRS), Laine, Elodie, and Lopes, Anne

Subjects
0301 basic medicine, Research design, [SDV]Life Sciences [q-bio], Social Sciences, Cloud computing, Biochemistry, Computational biology, Database and Informatics Methods, Sociology, Jury, Nothing, ComputingMilieux_COMPUTERSANDEDUCATION, Macromolecular Structure Analysis, Biology (General), media_common, Schools, Ecology, 4. Education, Professions, Computational Theory and Mathematics, Research Design, Modeling and Simulation, Lectures, Engineering ethics, Computer and Information Sciences, Universities, QH301-705.5, Bioinformatics, media_common.quotation_subject, Research and Analysis Methods, Education, 03 medical and health sciences, Cellular and Molecular Neuroscience, [ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM], Genetics, Humans, Students, Molecular Biology, Ecology, Evolution, Behavior and Systematics, business.industry, Research, Biology and Life Sciences, Proteins, Teachers, Coopetition, Computing Methods, 030104 developmental biology, Protein structure prediction, People and Places, Protein structure, Population Groupings, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], business
Abstract

This is a PLOS Computational Biology Education paper.; International audience; We present a new educational initiative, called Meet-U, that aims at training students to collaborativework in computational biology and at bridging the gap between education and research.Meet-U mimics the set up of collaborative research projects and takes advantage of the most populartools for collaborative work and of cloud computing. Students are grouped in teams of 4-5 peopleand have to realize a project from A to Z that answers a challenging question in Biology.Meet-U promotes "coopetition", as the students collaborate within and across the teams and are also incompetition with each other to develop the best final product.Meet-U fosters interactions between different actors of education and research through the organization of a meeting day, open to everyone, where the students present their work to a jury of researchers and jury members give researchseminars. This very unique combination of education and research is strongly motivating for thestudents and provides a formidable opportunity for a scientific community to unite and increase itsvisibility. We report on our experience with Meet-U in two French universities with master studentsin bioinformatics and modeling, with protein-protein docking as the subject of the course.Meet-U is easy to implement, virtually costs nothing and can be straightforwardly transferred to other fieldsand/or universities. All the information and data are available at http://www.meet-u.org.

Published
2018
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