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

Anna Niarakis (1, 2) , Marek Ostaszewski (3) , Alexander Mazein (3) , Inna Kuperstein (4, 5) , Martina Kutmon (6) , Marc E Gillespie (7) , Akira Funahashi (8) , Marcio Luis Acencio (9) , Ahmed Hemedan (9) , Michael Aichem (10) , Karsten Klein (10) , Tobias Czauderna (11) , Felicia Burtscher (3) , Takahiro G Yamada (8) , Yusuke Hiki (8) , Noriko F Hiroi (8, 12) , Finterly Hu (6) , Nhung Pham (6) , Friederike Ehrhart (13) , Egon L Willighagen (13) , Alberto Valdeolivas (14) , Aurelien Dugourd (14) , Francesco Messina (15) , Marina Esteban-Medina (16) , Maria Pena-Chilet (17, 16) , Kinza Rian , Sylvain Soliman (1) , Sara Sadat Aghamiri (18) , Bhanwar Lal Puniya (18) , Aurelien Naldi (1) , Tomas Helikar (18) , Vidisha Singh (2) , Marco Farinas Fernandez (19) , Viviam Bermudez (19) , Eirini Tsirvouli (19) , Arnau Montagud (20) , Vincent Noel (4, 5) , Miguel Ponce de Leon (20) , Dieter Maier , Angela Bauch , Benjamin M Gyori (21) , John A Bachman (21) , Agustin Luna (21) , Janet Pinero (22) , Laura I Furlong (22) , Irina Balaur (3) , Adrien Rougny (23) , Yohan Jarosz (3) , Rupert W Overall (24) , Robert Phair (25) , Livia Perfetto (26) , Lisa Matthews (27) , Devasahayam Arokia Balaya Rex (28) , Marija Orlic-Milacic , Luis Cristobal Monraz Gomez , Bertrand de Meulder , Jean Marie Ravel , Bijay Jassal , Venkata P Satagopam , Guanming Wu , Martin Golebiewski , Piotr Gawron , Laurence Calzone , Jacques S Beckmann , Chris T Evelo , Peter d'Eustachio , Falk Schreiber , Julio Saez-Rodriguez , Joaquin Dopazo , Martin Kuiper , Alfonso Valencia , Olaf Wolkenhauer , Hiroaki Kitano , Emmanuel Barillot , Charles Auffray , Rudi Balling , Reinhard Schneider

1 Lifeware - Computational systems biology and optimization
2 GenHotel - Laboratoire de recherche européen pour la polyarthrite rhumatoïde
3 University of Luxembourg [Luxembourg]
4 Cancer et génome: Bioinformatique, biostatistiques et épidémiologie d'un système complexe
5 PSL - Université Paris Sciences et Lettres
6 MaCSBio - Maastricht Centre for Systems Biology [Maastricht]
7 OICR - Ontario Institute for Cancer Research [Canada]
8 Keio University [Tokyo]
9 LCSB - Luxembourg Centre For Systems Biomedicine
10 University of Konstanz
11 Hochschule Mittweida - University of Applied Sciences
12 Kanagawa Institute of Technology
13 Maastricht University [Maastricht]
14 Heidelberg University Hospital [Heidelberg]
15 National Institute for Infectious Diseases "Lazzaro Spallanzani"
16 Hospital Universitario Virgen del Rocío [Sevilla]
17 Biomedicine Institute of Sevilla [Seville, Spain]
18 University of Nebraska–Lincoln
19 NTNU - Norwegian University of Science and Technology [Trondheim]
20 BSC-CNS - Barcelona Supercomputing Center - Centro Nacional de Supercomputacion
21 HMS - Harvard Medical School [Boston]
22 UPF - Universitat Pompeu Fabra [Barcelona]
23 AIST - National Institute of Advanced Industrial Science and Technology
24 HU Berlin - Humboldt-Universität zu Berlin = Humboldt University of Berlin = Université Humboldt de Berlin
25 Integrative Bioinformatics Inc [Mountain View]
26 Sapienza University of Rome - Department of Informatics and System Sciences
27 NYU Langone Medical Center - New York University Langone Medical Center
28 Yenepoya University

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.

Mots clés: SARS-CoV-2; systems biology; disease maps; mechanistic models; dynamic models; systems medicine; large-scale community effort

Domaines: Bio-informatique [q-bio.QM]

Anna Niarakis, Marek Ostaszewski, Alexander Mazein, Inna Kuperstein, Martina Kutmon, et al.. A versatile and interoperable computational framework for the analysis and modeling of COVID-19 disease mechanisms. 2022. ⟨hal-03907738⟩