Comparative Genomic Analysis of Bacterial Data in BV-BRC: An Example Exploring Antimicrobial Resistance.

Autor:	Wattam AR; Biocomplexity Institute, University of Virginia, Charlottesville, VA, USA. wattam@virginia.edu., Bowers N; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA.; Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL, USA., Brettin T; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA.; Computing, Environment and Life Sciences, Argonne National Laboratory, Argonne, IL, USA., Conrad N; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA.; Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL, USA., Cucinell C; Biocomplexity Institute, University of Virginia, Charlottesville, VA, USA., Davis JJ; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA.; Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL, USA., Dickerman AW; Biocomplexity Institute, University of Virginia, Charlottesville, VA, USA., Dietrich EM; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA.; Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL, USA., Kenyon RW; Biocomplexity Institute, University of Virginia, Charlottesville, VA, USA., Machi D; Biocomplexity Institute, University of Virginia, Charlottesville, VA, USA., Mao C; Biocomplexity Institute, University of Virginia, Charlottesville, VA, USA., Nguyen M; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA.; Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL, USA., Olson RD; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA.; Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL, USA., Overbeek R; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA.; Fellowship for Interpretation of Genomes, Burr Ridge, IL, USA., Parrello B; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA.; Fellowship for Interpretation of Genomes, Burr Ridge, IL, USA., Pusch GD; Fellowship for Interpretation of Genomes, Burr Ridge, IL, USA., Shukla M; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA.; Division of Data Science and Learning, Argonne National Laboratory, Argonne, IL, USA., Stevens RL; Department of Computer Science, University of Chicago, Chicago, IL, USA., Vonstein V; Fellowship for Interpretation of Genomes, Burr Ridge, IL, USA., Warren AS; Biocomplexity Institute, University of Virginia, Charlottesville, VA, USA.
Jazyk:	angličtina
Zdroj:	Methods in molecular biology (Clifton, N.J.) [Methods Mol Biol] 2024; Vol. 2802, pp. 547-571.
DOI:	10.1007/978-1-0716-3838-5_18
Abstrakt:	As genomic and related data continue to expand, research biologists are often hampered by the computational hurdles required to analyze their data. The National Institute of Allergy and Infectious Diseases (NIAID) established the Bioinformatics Resource Centers (BRC) to assist researchers with their analysis of genome sequence and other omics-related data. Recently, the PAThosystems Resource Integration Center (PATRIC), the Influenza Research Database (IRD), and the Virus Pathogen Database and Analysis Resource (ViPR) BRCs merged to form the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) at https://www.bv-brc.org/ . The combined BV-BRC leverages the functionality of the original resources for bacterial and viral research communities with a unified data model, enhanced web-based visualization and analysis tools, and bioinformatics services. Here we demonstrate how antimicrobial resistance data can be analyzed in the new resource. (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)
Databáze:	MEDLINE
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