COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms
Abstract 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. We discuss the tools, platforms, and guidelines necessary for the distributed development of its contents by a multi-faceted community of biocurators, domain experts, bioinformaticians, and computational biologists. We highlight the role of relevant databases and text mining approaches in enrichment and validation of the curated mechanisms. We describe the contents of the Map and their relevance to the molecular pathophysiology of COVID-19 and the analytical and computational modelling approaches that can be applied for mechanistic data interpretation and predictions. We conclude by demonstrating concrete applications of our work through several use cases and highlight new testable hypotheses..
Medienart: |
Preprint |
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Erscheinungsjahr: |
2023 |
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Erschienen: |
2023 |
Enthalten in: |
bioRxiv.org - (2023) vom: 10. Okt. Zur Gesamtaufnahme - year:2023 |
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Sprache: |
Englisch |
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Links: |
Volltext [kostenfrei] |
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Themen: |
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doi: |
10.1101/2020.10.26.356014 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
XBI019234821 |
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100 | 1 | |a Ostaszewski, Marek |e verfasserin |0 (orcid)0000-0003-1473-370X |4 aut | |
245 | 1 | 0 | |a COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms |
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520 | |a Abstract 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. We discuss the tools, platforms, and guidelines necessary for the distributed development of its contents by a multi-faceted community of biocurators, domain experts, bioinformaticians, and computational biologists. We highlight the role of relevant databases and text mining approaches in enrichment and validation of the curated mechanisms. We describe the contents of the Map and their relevance to the molecular pathophysiology of COVID-19 and the analytical and computational modelling approaches that can be applied for mechanistic data interpretation and predictions. We conclude by demonstrating concrete applications of our work through several use cases and highlight new testable hypotheses. | ||
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