A versatile and interoperable computational framework for the analysis and modeling of COVID-19 disease mechanisms-Reference-Cited by-同舟云学术

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

Published:2022-12-19 Issue: Volume: Page:
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Niarakis Anna^ORCID,Ostaszewski Marek^ORCID,Mazein Alexander^ORCID,Kuperstein Inna^ORCID,Kutmon Martina^ORCID,Gillespie Marc E.^ORCID,Funahashi Akira^ORCID,Acencio Marcio Luis^ORCID,Hemedan Ahmed^ORCID,Aichem Michael^ORCID,Klein Karsten^ORCID,Czauderna Tobias^ORCID,Burtscher Felicia^ORCID,Yamada Takahiro G.^ORCID,Hiki Yusuke^ORCID,Hiroi Noriko F.^ORCID,Hu Finterly^ORCID,Pham Nhung^ORCID,Ehrhart Friederike^ORCID,Willighagen Egon L.^ORCID,Valdeolivas Alberto^ORCID,Dugourd Aurelien,Messina Francesco^ORCID,Esteban-Medina Marina^ORCID,Peña-Chilet Maria^ORCID,Rian Kinza^ORCID,Soliman Sylvain^ORCID,Aghamiri Sara Sadat^ORCID,Puniya Bhanwar Lal,Naldi Aurélien^ORCID,Helikar Tomáš^ORCID,Singh Vidisha^ORCID,Fernández Marco Fariñas^ORCID,Bermudez Viviam,Tsirvouli Eirini^ORCID,Montagud Arnau^ORCID,Noël Vincent^ORCID,de Leon Miguel Ponce^ORCID,Maier Dieter^ORCID,Bauch Angela^ORCID,Gyori Benjamin M.^ORCID,Bachman John A.^ORCID,Luna Augustin,Pinero Janet,Furlong Laura I.^ORCID,Balaur Irina^ORCID,Rougny Adrien^ORCID,Jarosz Yohan^ORCID,Overall Rupert W.^ORCID,Phair Robert^ORCID,Perfetto Livia^ORCID,Matthews Lisa,Rex Devasahayam Arokia Balaya^ORCID,Orlic-Milacic Marija^ORCID,Cristobal Monraz Gomez Luis^ORCID,De Meulder Bertrand^ORCID,Ravel Jean Marie^ORCID,Jassal Bijay^ORCID,Satagopam Venkata^ORCID,Wu Guanming^ORCID,Golebiewski Martin^ORCID,Gawron Piotr^ORCID,Calzone Laurence^ORCID,Beckmann Jacques S.^ORCID,Evelo Chris T.^ORCID,D’Eustachio Peter^ORCID,Schreiber Falk^ORCID,Saez-Rodriguez Julio^ORCID,Dopazo Joaquin^ORCID,Kuiper Martin^ORCID,Valencia Alfonso^ORCID,Wolkenhauer Olaf^ORCID,Kitano Hiroaki^ORCID,Barillot Emmanuel^ORCID,Auffray Charles^ORCID,Balling Rudi^ORCID,Schneider Reinhard^ORCID,

Abstract

AbstractThe 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.

Publisher

Cold Spring Harbor Laboratory

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