TY - JOUR
AU - Ostaszewski, Marek
AU - Niarakis, Anna
AU - Mazein, Alexander
AU - Kuperstein, Inna
AU - Phair, Robert
AU - Orta-Resendiz, Aurelio
AU - Singh, Vidisha
AU - Aghamiri, Sara Sadat
AU - Acencio, Marcio Luis
AU - Glaab, Enrico
AU - Ruepp, Andreas
AU - Fobo, Gisela
AU - Montrone, Corinna
AU - Brauner, Barbara
AU - Frishman, Goar
AU - Monraz Gómez, Luis Cristóbal
AU - Somers, Julia
AU - Hoch, Matti
AU - Kumar Gupta, Shailendra
AU - Scheel, Julia
AU - Borlinghaus, Hanna
AU - Czauderna, Tobias
AU - Schreiber, Falk
AU - Montagud, Arnau
AU - Ponce de Leon, Miguel
AU - Funahashi, Akira
AU - Hiki, Yusuke
AU - Hiroi, Noriko
AU - Yamada, Takahiro G
AU - Dräger, Andreas
AU - Renz, Alina
AU - Naveez, Muhammad
AU - Bocskei, Zsolt
AU - Messina, Francesco
AU - Börnigen, Daniela
AU - Fergusson, Liam
AU - Conti, Marta
AU - Rameil, Marius
AU - Nakonecnij, Vanessa
AU - Vanhoefer, Jakob
AU - Schmiester, Leonard
AU - Wang, Muying
AU - Ackerman, Emily E
AU - Shoemaker, Jason E
AU - Zucker, Jeremy
AU - Oxford, Kristie
AU - Teuton, Jeremy
AU - Kocakaya, Ebru
AU - Summak, Gökçe Yağmur
AU - Hanspers, Kristina
AU - Kutmon, Martina
AU - Coort, Susan
AU - Eijssen, Lars
AU - Ehrhart, Friederike
AU - Rex, Devasahayam Arokia Balaya
AU - Slenter, Denise
AU - Martens, Marvin
AU - Pham, Nhung
AU - Haw, Robin
AU - Jassal, Bijay
AU - Matthews, Lisa
AU - Orlic-Milacic, Marija
AU - Senff Ribeiro, Andrea
AU - Rothfels, Karen
AU - Shamovsky, Veronica
AU - Stephan, Ralf
AU - Sevilla, Cristoffer
AU - Varusai, Thawfeek
AU - Ravel, Jean-Marie
AU - Fraser, Rupsha
AU - Ortseifen, Vera
AU - Marchesi, Silvia
AU - Gawron, Piotr
AU - Smula, Ewa
AU - Heirendt, Laurent
AU - Satagopam, Venkata
AU - Wu, Guanming
AU - Riutta, Anders
AU - Golebiewski, Martin
AU - Owen, Stuart
AU - Goble, Carole
AU - Hu, Xiaoming
AU - Overall, Rupert
AU - Maier, Dieter
AU - Bauch, Angela
AU - Gyori, Benjamin M
AU - Bachman, John A
AU - Vega, Carlos
AU - Grouès, Valentin
AU - Vazquez, Miguel
AU - Porras, Pablo
AU - Licata, Luana
AU - Iannuccelli, Marta
AU - Sacco, Francesca
AU - Nesterova, Anastasia
AU - Yuryev, Anton
AU - de Waard, Anita
AU - Turei, Denes
AU - Luna, Augustin
AU - Babur, Ozgun
AU - Soliman, Sylvain
AU - Valdeolivas, Alberto
AU - Esteban-Medina, Marina
AU - Peña-Chilet, Maria
AU - Rian, Kinza
AU - Helikar, Tomáš
AU - Puniya, Bhanwar Lal
AU - Modos, Dezso
AU - Treveil, Agatha
AU - Olbei, Marton
AU - De Meulder, Bertrand
AU - Ballereau, Stephane
AU - Dugourd, Aurélien
AU - Naldi, Aurélien
AU - Noël, Vincent
AU - Calzone, Laurence
AU - Sander, Chris
AU - Demir, Emek
AU - Korcsmaros, Tamas
AU - Freeman, Tom C
AU - Augé, Franck
AU - Beckmann, Jacques S
AU - Hasenauer, Jan
AU - Wolkenhauer, Olaf
AU - Wilighagen, Egon L
AU - Pico, Alexander R
AU - Evelo, Chris T
AU - Gillespie, Marc E
AU - Stein, Lincoln D
AU - Hermjakob, Henning
AU - D'Eustachio, Peter
AU - Saez-Rodriguez, Julio
AU - Dopazo, Joaquin
AU - Valencia, Alfonso
AU - Kitano, Hiroaki
AU - Barillot, Emmanuel
AU - Auffray, Charles
AU - Balling, Rudi
AU - Schneider, Reinhard
TI - COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.
JO - Molecular systems biology
VL - 17
IS - 10
SN - 1744-4292
CY - Heidelberg
PB - EMBO Press
M1 - DZNE-2021-01564
SP - e10387
PY - 2021
N1 - (CC BY)
AB - We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.
KW - COVID-19 Drug Treatment
KW - Antiviral Agents: therapeutic use
KW - COVID-19: drug therapy
KW - COVID-19: genetics
KW - COVID-19: immunology
KW - COVID-19: virology
KW - Computational Biology: methods
KW - Computer Graphics
KW - Cytokines: genetics
KW - Cytokines: immunology
KW - Data Mining: statistics & numerical data
KW - Databases, Factual
KW - Gene Expression Regulation
KW - Host Microbial Interactions: genetics
KW - Host Microbial Interactions: immunology
KW - Humans
KW - Immunity, Cellular: drug effects
KW - Immunity, Humoral: drug effects
KW - Immunity, Innate: drug effects
KW - Lymphocytes: drug effects
KW - Lymphocytes: immunology
KW - Lymphocytes: virology
KW - Metabolic Networks and Pathways: genetics
KW - Metabolic Networks and Pathways: immunology
KW - Myeloid Cells: drug effects
KW - Myeloid Cells: immunology
KW - Myeloid Cells: virology
KW - Protein Interaction Mapping
KW - SARS-CoV-2: drug effects
KW - SARS-CoV-2: genetics
KW - SARS-CoV-2: immunology
KW - SARS-CoV-2: pathogenicity
KW - Signal Transduction
KW - Software
KW - Transcription Factors: genetics
KW - Transcription Factors: immunology
KW - Viral Proteins: genetics
KW - Viral Proteins: immunology
KW - computable knowledge repository (Other)
KW - large-scale biocuration (Other)
KW - omics data analysis (Other)
KW - open access community effort (Other)
KW - systems biomedicine (Other)
KW - Antiviral Agents (NLM Chemicals)
KW - Cytokines (NLM Chemicals)
KW - Transcription Factors (NLM Chemicals)
KW - Viral Proteins (NLM Chemicals)
LB - PUB:(DE-HGF)16
C6 - pmid:34664389
C2 - pmc:PMC8524328
DO - DOI:10.15252/msb.202110387
UR - https://pub.dzne.de/record/162909
ER -