Networks and Molecular Biology
Réseaux et biologie moléculaire
2 – 6 March 2020
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Scientific Committee
Comité scientifique Alain Barrat (CNRS – CPT, Aix-Marseille Université) Organizing Committee
Comité d’organisation Anaïs Baudot (MMG, Aix-Marseille Université) For any further informations, contact |
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Networks (aka. maps or graphs) provide a powerful framework to represent and model the relationships between the elements of biological systems. Indeed, networks can encompass a wide variety of biological information such as genetic or transcriptional regulation, protein-protein interaction, metabolic or signaling pathways, for instance. The nodes of the network typically represent the biological components, whereas edges represent interactions between them. The resulting systems are highly complex, display emerging properties, and prevent a simple direct interpretation. The field of network biology is highly dynamic and challenging. The week will be organized around 3 theoretical themes. First, Network modeling to simulate the cellular dynamics. Then, to leverage the recent and abundant -omics data, we will focus on Network inference approaches, and, finally, Network mining strategies.
The global aim of the conference is to present both (i) theoretical models and (ii) applications of these approaches to biomedicine, in particular rare diseases and cancer. Keywords: Biological networks – Graph theory – Discrete mathematical modeling – Big data – Omics – Statistical Inference – Machine learning |
Les réseaux (aussi appelés cartes ou graphes) fournissent un cadre puissant pour représenter et modéliser les relations entre les éléments des systèmes biologiques. En effet, les réseaux peuvent englober une grande variété d’informations biologiques telles que la régulation génétique ou transcriptionnelle, l’interaction protéines-protéines, les voies métaboliques ou de signalisation, par exemple. Les nœuds du réseau représentent généralement les composantes biologiques, tandis que les bords représentent les interactions entre eux. Les systèmes qui en résultent sont très complexes, présentent des propriétés émergentes et empêchent une simple interprétation directe. Le domaine de la biologie des réseaux est très dynamique et stimulant. La semaine sera organisée autour de 3 thèmes théoriques. Tout d’abord, la modélisation du réseau pour simuler la dynamique cellulaire. Ensuite, pour tirer parti des données récentes et abondantes sur les -omiques, nous nous concentrerons sur les approches d’inférence du Réseau et, enfin, sur les stratégies minières du Réseau.
L’objectif global de la conférence est de présenter à la fois (i) des modèles théoriques et (ii) des applications de ces approches à la biomédecine, en particulier aux maladies rares et au cancer. Mots-clés : Réseaux biologiques – Théorie des graphes – Modélisation mathématique discrète – Grandes données – Omics – Inférence statistique – Apprentissage machine |
Chloé-Agathe Azencott (Mines ParisTech – Institut Curie, Paris) Network-guided feature selection in high-dimensional genomic data
Christine Brun (TAGC, Marseille) From Data to Biological Processes: Interactions, Networks and Analyses, to understand Cellular Functions
Stefani Dritsa (IMAGINE – Institut des Maladies Génétiques, Paris) Machine learning for disease gene identification: graph-based approaches
Hervé Isambert (Institut Curie, Paris) Learning interpretable networks from multivariate information in biological and clinical data
Edda Klipp (Humboldt University, Berlin) Cell Processes in Space and Time — Exemplified with Yeast Mating
Kim-Anh Lê Cao (University of Melbourne) Matrix factorisation techniques for data integration and the identification of gene modules
Maria Rodriguez-Martinez (IBM, Zurich) Network approaches for personalized medicine
Julio Saez-Rodriguez (European Bioinformatics Institute, Cambridge) Networks of prior knowledge as frames to understand complex biological data (Part 1) & Dynamic logic models complement machine learning for personalized medicine (part 2)
Jana Wolf (Max Delbrück Center, Germany) Modelling signal transduction and gene regulation at the interface of single-cell and population data
Talks
Stephen Chapman (University of Manchester) Flux Balance Analysis of a Mesenchymal Stem Cell predicts changing global metabolism with ROS induced by alpha-ketogluterate dehydrogenase activity
Stéphanie Chevalier (Université Paris-Sud) Synthesis of Boolean Networks from Biological Dynamical Constraints using Answer-Set Programming
Ulysse Herbach (Institut Elie Cartan de Lorraine & Inria Nancy) Inferring gene networks with single-cell data: from mechanistic modelling to statistics
Peter Hoitinga (University of Groningen) Detecting gene co-option in co-expression data
Takoua Jendoubi (Imperial College London) Decomposing multivariate association measures into networks for omics integrative analysis
Maxime Lucas (Aix-Marseille Université) The budding yeast cell cycle as a temporal network of protein interactions
Elva-Maria Novoa-del-Toro (Aix-Marseille Université) A Multi-Objective Genetic Algorithm to Find Active Contr. talk Subnetworks from Multiplex Biological Networks
Iker Nunez Carpintero (Barcelona Supercomputing Center) A multilayer network approach to elucidate severity in Congenital Myasthenic Syndromes
Ozan Ozisik (Aix-Marseille Université) Computing the network impact of interaction losses in laminopathies with a random walk with restart
Lé o Pio-Lopez (Aix-Marseille Université) MultiVERSE: a graph representation learning approach for multiplex networks
Clémence Réda (Université Paris Diderot) Automated Inference of Gene Regulatory Networks Using Explicit Regulatory Modules
Romain Yvinec (Université François Rabelais de Tours) Kinetic biased signaling: towards a system biology definition of drugs selectivity. Illustration on the Follicle Stimulating Hormone Receptor
Posters
Olivia Angelin-Bonnet, Susan Thomson, Samantha Baldwin, Patrick J. Biggs and Matthieu Vignes
Stochastic simulations of gene regulatory networks with sismonr
Anthony Baptista, Anaïs Baudot and Aitor Gonzalez
Studying relationships between rare and common diseases with multilayer genomic, molecular and disease networks
Kieran Elmes, Anaïs Baudot, Elisabeth Remy and Matthieu Vignes
Infering functional module from protein interaction and gene expression
Ana Fonseca, Pedro T. Monteiro, Miguel C. Teixeira, Claudine Chaouiya
Stochastic simulations of gene regulatory networks with sismonr
Jérémie Grignard, Thierry Dorval and François Fagès
The tyrosination post-translational modi cation is mainly regulated by detyrosination and depolymerizing factors: possible role in neurodegenerative
diseases
Léonard Hérault, Adrien Mazuel, Mathilde Poplineau, Nadine Platet, Elisabeth Remy and Estelle Duprez
Analysis of early hematopoiesis aging with single-cell RNA seq
Marine Louarn
Increasing life science resources re-usability using Semantic Web technologies
Julien Martinelli, Jérémie Grignard, Sylvain Solivan and François Fagès
A Statistical Unsupervised Learning Algorithm for Inferring Reaction Networks from Time Series Data
Laurent Naudin
Development of system biology pipelines for the discovery of drug combinations in cancer
Saran Pankaew, Delphine Potier, Marie Loosveld, Elisabeth Remy and Dominque Payet Bornet
Systems biology approach to model PTEN & TCR signaling network in thymocytes
Marianyela Petrizzelli
Towards Identification of Differentiation Potency
Kirsten Thobe, Alisa Fuchs, Yozlem Bahar, Robert Zinzen, Jana Wolf
Logical modeling of neuroectoderm specification in Drosophila
Nina Verstraete, Helene Arduin, Marcin Domagala, Mary Poupot and Vera Pancaldi
Modelling the differentiation dynamics of monocytes in contact with BCLL cancer cells
Meline Wery, Emmanuelle Becker, Franck Auge, Charles Bettembourg, Olivier Dameron and Anne Siegel
Query-based approach for generating candidates for epistasis regulation from clinical paired multiomics data
