Deep models of integrated multiscale molecular data decipher the endothelial cell response to ionizing radiation
Ian Morilla, Philippe Chan, Fanny Caffin, Ljubica Svilar, Sonia Selbonne, Ségolène Ladaigue, V. Buard, Georges Tarlet, Béatrice Micheau, Vincent Paget, Agnès François, Maâmar Souidi, Jean‐Charles Martin, David Vaudry, Mohamed Amine Benadjaoud, Fabien Milliat, Olivier Guipaud
Abstract
. We then designed a strategy of deep learning as in convolutional graph networks that facilitates unsupervised high-level feature extraction of important omics data to learn how ionizing radiation-induced endothelial dysfunction may evolve over time. Last, we present experimental data showing that some of the features identified using our approach are involved in the alteration of angiogenesis by ionizing radiation.
Topics & Concepts
Ionizing radiationTranscriptomeMetabolomeComputational biologyProteomeBiologyDECIPHERBioinformaticsMetabolomicsCancer researchIrradiationBiochemistryPhysicsGene expressionGeneNuclear physicsBioinformatics and Genomic NetworksMetabolomics and Mass Spectrometry StudiesCell Image Analysis Techniques