5 results on '"Marcus Chibucos"'
Search Results
2. Investigation of an outbreak of COVID-19 among U.S. military personnel and beneficiaries stationed in the Republic of Korea, June-July 2021.
- Author
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Shilpa Hakre, Evelyn Y Lam, Irina Maljkovic-Berry, Jun Hang, Luis A Pow Sang, Elizabeth J Bianchi, Christian Fung, Jay Gandhi, Marcus Chibucos, Matthew A Conte, Adam R Pollio, Christine A Mariskanish, Luke A Mansfield, Kayvon Modjarrad, Heather L Friberg-Robertson, Grace M Lidl, Paul T Scott, and Douglas A Lougee
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Public aspects of medicine ,RA1-1270 - Abstract
On 28 May 2021, leisure travel restrictions in place to control coronavirus disease 2019 (COVID-19) were eased among vaccinated U.S. military personnel and beneficiaries stationed in South Korea (USFK) allowing access to bars and clubs which were off limits. We describe results from an investigation of the largest severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak as of November 2021 among USFK personnel following this change in policy. Data such as SARS-CoV-2 real-time polymerase chain reaction (RT-PCR) test results, demographic characteristics, symptom and vaccination histories, and genome sequences were analyzed. Of a total 207 new cases of COVID-19 diagnosed among USFK members from 15 June to 27 July 2021, 113 (57%) eligible cases were fully vaccinated, of whom 86 (76%) were symptomatic. RT-PCR cycling threshold values were similar among vaccinated and unvaccinated members. Whole genomic sequencing of 54 outbreak samples indicated all infections were due to the Delta variant. Phylogenetic analysis revealed two sources of SARS-CoV-2 accounted for 41% of infections among vaccinated and unvaccinated members. Vaccinated personnel were not at risk of severe illness; however, 86% experienced symptoms following infection. There were no hospitalizations among COVID-19 cases, most of whom were young military service members. Rescinded restrictions were reinstated to control the outbreak. Masking was mandated among all personnel predating U.S. national recommendations for indoor masking in high COVID-19 transmission areas. Increased vaccination with continued vigilance and extension of COVID-19 mitigation measures are warranted to contain the spread of SARS-CoV-2 variants of concern.
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- 2022
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3. ECO: the Evidence and Conclusion Ontology, an update for 2022
- Author
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Suvarna Nadendla, Rebecca Jackson, James Munro, Federica Quaglia, Bálint Mészáros, Dustin Olley, Elizabeth T Hobbs, Stephen M Goralski, Marcus Chibucos, Christopher John Mungall, Silvio C E Tosatto, Ivan Erill, and Michelle G Giglio
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Gene Ontology ,AcademicSubjects/SCI00010 ,Databases, Genetic ,Genetics ,Computational Biology ,Humans ,Database Issue ,Molecular Sequence Annotation ,Software - Abstract
The Evidence and Conclusion Ontology (ECO) is a community resource that provides an ontology of terms used to capture the type of evidence that supports biomedical annotations and assertions. Consistent capture of evidence information with ECO allows tracking of annotation provenance, establishment of quality control measures, and evidence-based data mining. ECO is in use by dozens of data repositories and resources with both specific and general areas of focus. ECO is continually being expanded and enhanced in response to user requests as well as our aim to adhere to community best-practices for ontology development. The ECO support team engages in multiple collaborations with other ontologies and annotating groups. Here we report on recent updates to the ECO ontology itself as well as associated resources that are available through this project. ECO project products are freely available for download from the project website (https://evidenceontology.org/) and GitHub (https://github.com/evidenceontology/evidenceontology). ECO is released into the public domain under a CC0 1.0 Universal license.
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- 2022
4. Expansion of the Gene Ontology knowledgebase and resources
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Ray Stefancsik, James Balhoff, Marc Feuermann, Rex Chisholm, Kim Rutherford, Nicholas Brown, Rachael Huntley, Sabrina Toro, Ivo Pedruzzi, Valerie Wood, Barbara Kramarz, Nancy Campbell, Alexander Deng, Sandip Patel, Paul Thomas, Ruth Lovering, James Hu, Cathy Wu, Kevin Howe, Jurg Bahler, Midori Harris, Michele Magrane, Giulia Antonazzo, Matthew Berriman, Paola Roncaglia, Petra Fey, J. Michael Cherry, Susan Tweedie, Jane Lomax, Marcus Chibucos, and Peter McQuilton
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0301 basic medicine ,media_common.quotation_subject ,Biology ,Ontology (information science) ,Web Browser ,Bioinformatics ,03 medical and health sciences ,0302 clinical medicine ,Resource (project management) ,Research community ,Databases, Genetic ,Genetics ,Database Issue ,Quality (business) ,Phylogeny ,Causal model ,media_common ,Gene ontology ,Computational Biology ,Molecular Sequence Annotation ,Genomics ,Data science ,030104 developmental biology ,Gene Ontology ,030217 neurology & neurosurgery ,Biological network - Abstract
The Gene Ontology (GO) is a comprehensive resource of computable knowledge regarding the functions of genes and gene products. As such, it is extensively used by the biomedical research community for the analysis of -omics and related data. Our continued focus is on improving the quality and utility of the GO resources, and we welcome and encourage input from researchers in all areas of biology. In this update, we summarize the current contents of the GO knowledgebase, and present several new features and improvements that have been made to the ontology, the annotations and the tools. Among the highlights are 1) developments that facilitate access to, and application of, the GO knowledgebase, and 2) extensions to the resource as well as increasing support for descriptions of causal models of biological systems and network biology. To learn more, visit http://geneontology.org/.
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- 2016
5. Gene Ontology Consortium: going forward
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Lisa Matthews, Rex Chisholm, Philippa Talmud, Paul Denny, Lionel Breuza, Kim Rutherford, Antonia Lock, Nicholas Brown, Rachael Huntley, Tanya Berardini, Rebecca Foulger, Paul Kersey, Peter D'Eustachio, Ivo Pedruzzi, Valerie Wood, Diane Inglis, Paul Lloyd, Daniel Staines, Michael Tognolli, Nancy Campbell, Emmanuel Boutet, Alice Dashow, Mark McDowall, Claire O'Donovan, Deborah Siegele, Pascale Gaudet, Paul Thomas, Ruth Lovering, James Hu, Janos Demeter, Patrick Masson, Cathy Wu, Alex Bateman, Jurg Bahler, Emma Hatton-Ellis, Midori Harris, Michele Magrane, Anne Estreicher, Alan Bridge, Suzi Aleksander, Paola Roncaglia, Eva Huala, Robert Finn, Petra Fey, J. Michael Cherry, Susan Tweedie, David Osumi-Sutherland, Jane Lomax, Benoit Bely, Ramona Britto, Joanna Argasinska, Stacia Engel, Elena Cibrián Uhalte, Prudence Mutowo, Sylvain Poux, Maria-Jesus Martin, Catherine Rivoire, Elisabeth Coudert, Helen Parkinson, Stephen E Humphries, Penelope Garmiri, Amaia Sangrador, Paul Gane, Marcus Chibucos, Helen Attrill, Klemens Pichler, Cecilia Arighi, and Maxim Scheremetjew
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Internet ,Process ontology ,Ontology-based data integration ,Cell Cycle ,Suggested Upper Merged Ontology ,Molecular Sequence Annotation ,Ontology (information science) ,Biology ,Bioinformatics ,Metadata ,World Wide Web ,Open Biomedical Ontologies ,Documentation ,Gene Ontology ,Databases, Genetic ,Genetics ,Database Issue ,Upper ontology ,ComputingMethodologies_GENERAL ,ddc:576 - Abstract
The Gene Ontology (GO; http://www.geneontology.org) is a community-based bioinformatics resource that supplies information about gene product function using ontologies to represent biological knowledge. Here we describe improvements and expansions to several branches of the ontology, as well as updates that have allowed us to more efficiently disseminate the GO and capture feedback from the research community. The Gene Ontology Consortium (GOC) has expanded areas of the ontology such as cilia-related terms, cell-cycle terms and multicellular organism processes. We have also implemented new tools for generating ontology terms based on a set of logical rules making use of templates, and we have made efforts to increase our use of logical definitions. The GOC has a new and improved web site summarizing new developments and documentation, serving as a portal to GO data. Users can perform GO enrichment analysis, and search the GO for terms, annotations to gene products, and associated metadata across multiple species using the all-new AmiGO 2 browser. We encourage and welcome the input of the research community in all biological areas in our continued effort to improve the Gene Ontology.
- Published
- 2015
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