التفاصيل البيبلوغرافية
| العنوان: |
COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms |
| المؤلفون: |
Fonds National de la Recherche Luxembourg, European Commission, Federal Ministry of Education and Research (Germany), Ministry of Science, Research and Art Baden-Württemberg, German Center for Infection Research, Netherlands Organisation for Health Research and Development, National Institutes of Health (US), European Molecular Biology Laboratory, Ostaszewski, Marek, Niarakis, Anna, Mazein, Alexander, Kuperstein, Inna, Phair, Robert, Orta-Resendiz, Aurelio, Singh, Vidisha, Aghamiri, Sara Sadat, Acencio, Marcio Luis, Glaab, Enrico, Ruepp, Andreas, Schreiber, Falk, Montagud, Arnau, Ponce de León, Miguel, Funahashi, Akira, Hiki, Yusuke, Hiroi, Noriko, Yamada, Takahiro G., Dräger, Andreas, Renz, Alina, Naveez, Muhammad, Orlic-Milacic, Marija, Bocskei, Zsolt, Messina, Francesco, Börnigen, Daniela, Fergusson, Liam, Conti, Marta, Rameil, Marius, Nakonecnij, Vanessa, Vanhoefer, Jakob, Schmiester, Leonard, Wang, Muying, Senff Ribeiro, Andrea, Ackerman, Emily E., Shoemaker, Jason E., Zucker, Jeremy, Oxford, Kristie, Teuton, Jeremy, Kocakaya, Ebru, Summak, Gökçe Yagmu, Hanspers, Kristina, Kutmon, Martina, Coort, Susan, Rothfels, Karen, Eijssen, Lars, Ehrhart, Friederike, Arokia Balaya Rex, Devasahayam, Slenter, Denise, Martens, Marvin, Pham, Nhung, Haw, Robin, Jassal, Bijay, Matthews, Lisa, Shamovsky, Veronic, Stephan, Ralf, Sevilla, Cristoffer, Varusai, Thawfeek, Ravel, Jean-Marie, Fraser, Rupsha, Ortseifen, Vera, Soliman, Sylvain, Marchesi, Silvia, Gawron, Piotr, Smula, Ewa, Heirendt, Laurent, Satagopam, Venkata, Wu, Guanming, Riutta, Anders, Golebiewski, Martin, Owen, Stuart, Goble, Carole, Valdeolivas, Alberto, Hu, Xiaoming, Overall, Rupert W., Maier, Dieter, Bauch, Angela, Gyori, Benjamin M., Bachman, John A., Vega, Carlos, Groues, Valentin, Vázquez, Miguel, Porras, Pablo, Esteban-Medina, Marina, Licata, Luana, Iannuccelli, Marta, Sacco, Francesca, Nesterova, Anastasia, Yuryev, Anton, Waard, Anita de, Turei, Denes, Luna, Augustín, Babur, Ozgun, Peña-Chilet, María, Rian, Kinza, Helikar, Tomas, Lal Puniya, Bhanwar, Modos, Dezso, Treveil, Agatha, Olbe, Marton, Fobo, Gisela, De Meulder, Bertrand, Ballereau, Stephane, Dugourd, Aurelien, Naldi, Aurelien, Noël, Vincent, Calzone, Laurence, Sander, Chris, Demir, Emek, Korcsmaros, Tamas, Freeman, Tom C., Montrone, Corinna, Auge, Franck, Beckmann, Jacques S., Hasenauer, Jan, Wolkenhauer, Olaf, Wilighagen, Egon L ., Pico, Alexander R., Evelo, Chris T., Gillespie, Marc E., Stein, Lincoln D., Hermjakob, Henning, Brauner, Barbara, D’Eustachio, Peter, Sáez-Rodríguez, Julio, Dopazo, Joaquín, Valencia, Alfonso, Kitano, Hiroaki, Barillot, Emmanuel, Auffray, Charles, Balling, Rudi, Schneider, Reinhard, Frishman, Goar, Monraz Gómez, Luis Cristóbal, Somers, Julia, Hoch, Matti, Gupta, Shailendra Kumar, Scheel, Julia, Borlinghaus, Hanna, Czauderna, Tobias |
| بيانات النشر: |
EMBO Press 2021-10-19 |
| نوع الوثيقة: |
Electronic Resource |
| مستخلص: |
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. |
| مصطلحات الفهرس: |
computable knowledge repository, large-scale biocuration, omics data analysis, open access community effort, systems biomedicine, artículo |
| URL: |
http://hdl.handle.net/10261/269421
Publisher's version
http://dx.doi.org/10.15252/msb.202110387
Sí
info:eu-repo/grantAgreement/EC/H2020/825070
info:eu-repo/grantAgreement/EC/H2020/951773
info:eu-repo/grantAgreement/EC/H2020/765274 |
| الاتاحة: |
Open access content. Open access content
http://creativecommons.org/licenses/by/4.0
openAccess |
| Other Numbers: |
CTK oai:digital.csic.es:10261/269421
Molecular Systems Biology 17: e10387 (2021)
10.15252/msb.202110387
1333185278 |
| المصدر المساهم: |
CSIC
From OAIster®, provided by the OCLC Cooperative. |
| رقم الانضمام: |
edsoai.on1333185278 |
| قاعدة البيانات: |
OAIster |