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A versatile and interoperable computational framework for the analysis and modeling of COVID-19 disease mechanisms

Authors :
Niarakis, Anna
Ostaszewski, Marek
Mazein, Alexander
Kuperstein, Inna
Kutmon, Martina
Gillespie, Marc
Funahashi, Akira
Acencio, Marcio
Hemedan, Ahmed
Aichem, Michael
Klein, Karsten
Czauderna, Tobias
Burtscher, Felicia
Yamada, Takahiro
Hiki, Yusuke
Hiroi, Noriko
Hu, Finterly
Pham, Nhung
Ehrhart, Friederike
Willighagen, Egon
Valdeolivas, Alberto
Dugourd, Aurelien
Messina, Francesco
Esteban-Medina, Marina
Pena-Chilet, Maria
Rian, Kinza
Soliman, Sylvain
Aghamiri, Sara
Puniya, Bhanwar
Naldi, Aurelien
Helikar, Tomas
Singh, Vidisha
Farinas Fernandez, Marco
Bermudez, Viviam
Tsirvouli, Eirini
Montagud, Arnau
Noel, Vincent
Ponce de Leon, Miguel
Maier, Dieter
Bauch, Angela
Gyori, Benjamin
Bachman, John
Luna, Agustin
Pinero, Janet
Furlong, Laura
Balaur, Irina
Rougny, Adrien
Jarosz, Yohan
Overall, Rupert
Phair, Robert
Perfetto, Livia
Matthews, Lisa
Rex, Devasahayam
Orlic-Milacic, Marija
Monraz Gomez, Luis
de Meulder, Bertrand
Ravel, Jean
Jassal, Bijay
Satagopam, Venkata
Wu, Guanming
Golebiewski, Martin
Gawron, Piotr
Calzone, Laurence
Beckmann, Jacques
Evelo, Chris
d'Eustachio, Peter
Schreiber, Falk
Saez-Rodriguez, Julio
Dopazo, Joaquin
Kuiper, Martin
Valencia, Alfonso
Wolkenhauer, Olaf
Kitano, Hiroaki
Barillot, Emmanuel
Auffray, Charles
Balling, Rudi
Schneider, Reinhard
Computational systems biology and optimization (Lifeware)
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 recherche européen pour la polyarthrite rhumatoïde (GenHotel)
Université d'Évry-Val-d'Essonne (UEVE)-Université Paris-Saclay
University of Luxembourg [Luxembourg]
Cancer et génome: Bioinformatique, biostatistiques et épidémiologie d'un système complexe
Mines Paris - PSL (École nationale supérieure des mines de Paris)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM)
Université Paris sciences et lettres (PSL)
Maastricht Centre for Systems Biology [Maastricht] (MaCSBio)
Maastricht University [Maastricht]
Ontario Institute for Cancer Research [Canada] (OICR)
Ontario Institute for Cancer Research
Keio University
Luxembourg Centre For Systems Biomedicine (LCSB)
University of Konstanz
Hochschule Mittweida - University of Applied Sciences
Kanagawa Institute of Technology
Heidelberg University Hospital [Heidelberg]
National Institute for Infectious Diseases 'Lazzaro Spallanzani'
Hospital Universitario Virgen del Rocío [Sevilla]
Biomedicine Institute of Sevilla [Seville, Spain]
University of Nebraska–Lincoln
University of Nebraska System
Norwegian University of Science and Technology [Trondheim] (NTNU)
Norwegian University of Science and Technology (NTNU)
Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS)
Harvard Medical School [Boston] (HMS)
Universitat Pompeu Fabra [Barcelona] (UPF)
National Institute of Advanced Industrial Science and Technology (AIST)
Humboldt University Of Berlin
Integrative Bioinformatics Inc [Mountain View]
Department of Informatics and System Sciences (Sapienza University of Rome)
Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome] (UNIROMA)
New York University Langone Medical Center (NYU Langone Medical Center)
NYU System (NYU)
Yenepoya University
Janet Piñero, Laura I. Furlong: IMI2-JU grants, resources which are composed of financial contributions from the European Union’s Horizon 2020 Research and Innovation Programme and EFPIA [GA: 777365 eTRANSAFE], and the EU H2020 Programme [GA:964537 RISKHUNT3R]
Project 001-P-001647—Valorisation of EGA for Industry and Society funded by the European Regional Development Fund (ERDF) and Generalitat de Catalunya
Institute of Health Carlos III (project IMPaCT-Data, exp. IMP/00019), co-funded by the European Union, European Regional Development Fund (ERDF, 'A way to make Europe').
Publication Year :
2022
Publisher :
HAL CCSD, 2022.

Abstract

The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Community-driven and highly interdisciplinary, the project is collaborative and supports community standards, open access, and the FAIR data principles. The coordination of community work allowed for an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework links key molecules highlighted from broad omics data analysis and computational modeling to dysregulated pathways in a cell-, tissue- or patient-specific manner. We also employ text mining and AI-assisted analysis to identify potential drugs and drug targets and use topological analysis to reveal interesting structural features of the map. The proposed framework is versatile and expandable, offering a significant upgrade in the arsenal used to understand virus-host interactions and other complex pathologies.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....26f407e3c68a11f2720278c05d9b19a6