22/03 - Laurent Tichit (IMM) : Random Walk with Restart on Multilayer Biological Networks

In this seminar, Dr. Laurent Tichit from Université D’aix-Marseille will present his work on random walk with restart on multilayer biological networks at Computational Biology and Bioinformatics Lab in Bordeaux

22/03 -  Laurent Tichit (IMM) : Random Walk with Restart on Multilayer Biological Networks
Network representation of the top 25 ranked genes and diseases when the RWR-MH algorithm is executed using WRS as seed
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Speaker: Laurent Tichit, Imm, Université D’aix-marseille
Title: Random Walk with Restart on Multilayer Biological Networks
Location: Centre de Génomique Fonctionnelle (salle des conférences, 1ème étage)
Date: TUESDAY 22 MARS 2022, 14h
Exemple of Multiplex, Heterogeneous and Multiplex-Heterogeneous graphs
Exemple of Multiplex, Heterogeneous and Multiplex-Heterogeneous graphs

Random walk with restart is the state-of-the-art guilt-by-association approach. It explores the network vicinity of gene/protein seeds to study their functions, based on the premise that nodes related to similar functions tend to lie close to each other in the networks.

We extended the RWR algorithm to multilayer networks. The walk can now explore different layers of physical and functional interactions between genes and proteins. It can also jump to a network containing different sets of edges and nodes, such as phenotype similarities between diseases. We devised a leave-one-out cross-validation strategy to evaluate the algorithms abilities to predict disease-associated genes. Finally, we applied the algorithm to predict candidate genes for two genetic diseases: the Wiedemann-Rautenstrauch progeroid syndrome and the SHORT syndrome.

Random walk with restart on multiplex and heterogeneous biological networks
Recent years have witnessed an exponential growth in the number of identified interactions between biological molecules. These interactions are usually represented as large and complex networks, calling for the development of appropriated tools to exploit the functional information they contain. Ran…
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