Web tools to fight pandemics: the COVID-19 experience
Abstract The current outbreak of COVID-19 has generated an unprecedented scientific response worldwide, with the generation of vast amounts of publicly available epidemiological, biological and clinical data. Bioinformatics scientists have quickly produced online methods to provide non-computational...
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| Veröffentlicht in: | Briefings in bioinformatics 2021-03, Vol.22 (2), p.690-700 |
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| container_title | Briefings in bioinformatics |
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| creator | Mercatelli, Daniele Holding, Andrew N Giorgi, Federico M |
| description | Abstract
The current outbreak of COVID-19 has generated an unprecedented scientific response worldwide, with the generation of vast amounts of publicly available epidemiological, biological and clinical data. Bioinformatics scientists have quickly produced online methods to provide non-computational users with the opportunity of analyzing such data. In this review, we report the results of this effort, by cataloguing the currently most popular web tools for COVID-19 research and analysis. Our focus was driven on tools drawing data from the fields of epidemiology, genomics, interactomics and pharmacology, in order to provide a meaningful depiction of the current state of the art of COVID-19 online resources. |
| doi_str_mv | 10.1093/bib/bbaa261 |
| format | Article |
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The current outbreak of COVID-19 has generated an unprecedented scientific response worldwide, with the generation of vast amounts of publicly available epidemiological, biological and clinical data. Bioinformatics scientists have quickly produced online methods to provide non-computational users with the opportunity of analyzing such data. In this review, we report the results of this effort, by cataloguing the currently most popular web tools for COVID-19 research and analysis. Our focus was driven on tools drawing data from the fields of epidemiology, genomics, interactomics and pharmacology, in order to provide a meaningful depiction of the current state of the art of COVID-19 online resources.</description><identifier>ISSN: 1467-5463</identifier><identifier>EISSN: 1477-4054</identifier><identifier>DOI: 10.1093/bib/bbaa261</identifier><identifier>PMID: 33057582</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Bioinformatics ; Computational Biology ; Computer applications ; Coronaviruses ; COVID-19 ; COVID-19 - prevention & control ; COVID-19 - virology ; Epidemiology ; Humans ; Internet ; Internet resources ; Method Review ; Pandemics ; Pharmacology ; SARS-CoV-2 - isolation & purification</subject><ispartof>Briefings in bioinformatics, 2021-03, Vol.22 (2), p.690-700</ispartof><rights>The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com 2020</rights><rights>The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.</rights><rights>The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c468t-52b9b2345ce40b5e378e340dc0597ebb36513968afd7774a10a9343888efe8bc3</citedby><cites>FETCH-LOGICAL-c468t-52b9b2345ce40b5e378e340dc0597ebb36513968afd7774a10a9343888efe8bc3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665357/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665357/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,1598,27901,27902,53766,53768</link.rule.ids><linktorsrc>$$Uhttps://dx.doi.org/10.1093/bib/bbaa261$$EView_record_in_Oxford_University_Press$$FView_record_in_$$GOxford_University_Press</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33057582$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mercatelli, Daniele</creatorcontrib><creatorcontrib>Holding, Andrew N</creatorcontrib><creatorcontrib>Giorgi, Federico M</creatorcontrib><title>Web tools to fight pandemics: the COVID-19 experience</title><title>Briefings in bioinformatics</title><addtitle>Brief Bioinform</addtitle><description>Abstract
The current outbreak of COVID-19 has generated an unprecedented scientific response worldwide, with the generation of vast amounts of publicly available epidemiological, biological and clinical data. Bioinformatics scientists have quickly produced online methods to provide non-computational users with the opportunity of analyzing such data. In this review, we report the results of this effort, by cataloguing the currently most popular web tools for COVID-19 research and analysis. 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The current outbreak of COVID-19 has generated an unprecedented scientific response worldwide, with the generation of vast amounts of publicly available epidemiological, biological and clinical data. Bioinformatics scientists have quickly produced online methods to provide non-computational users with the opportunity of analyzing such data. In this review, we report the results of this effort, by cataloguing the currently most popular web tools for COVID-19 research and analysis. Our focus was driven on tools drawing data from the fields of epidemiology, genomics, interactomics and pharmacology, in order to provide a meaningful depiction of the current state of the art of COVID-19 online resources.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>33057582</pmid><doi>10.1093/bib/bbaa261</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Briefings in bioinformatics, 2021-03, Vol.22 (2), p.690-700 |
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| language | eng |
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| source | Oxford Journals Open Access Collection |
| subjects | Bioinformatics Computational Biology Computer applications Coronaviruses COVID-19 COVID-19 - prevention & control COVID-19 - virology Epidemiology Humans Internet Internet resources Method Review Pandemics Pharmacology SARS-CoV-2 - isolation & purification |
| title | Web tools to fight pandemics: the COVID-19 experience |
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