A systematic bioinformatics approach for large-scale identification and characterization of host-pathogen shared sequences.

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James S. A., Ong H. S., Hari R., Khan A. M.

BMC genomics, vol.22, no.Suppl 3, pp.700, 2021 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 22 Issue: Suppl 3
  • Publication Date: 2021
  • Doi Number: 10.1186/s12864-021-07657-4
  • Journal Name: BMC genomics
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, EMBASE, Food Science & Technology Abstracts, MEDLINE, Veterinary Science Database, Directory of Open Access Journals
  • Page Numbers: pp.700
  • Keywords: Shared sequences, Share-ome, Host-pathogen, Bioinformatics, Large-scale, Methodology, Flaviviridae, Flavivirus, Hepacivirus, Pegivirus, Pestivirus, Dengue virus, West Nile virus, Hepatitis C virus, Cross-reactivity, Crossreactome, Peptide sharing, Peptide overlap, Molecular mimicry, CD-HIT, VIRUS, PROTEIN, DATABASE, HEMAGGLUTININ, AUTOIMMUNITY, DOMAINS, DISEASE, IMPACT, P53
  • Bezmialem Vakıf University Affiliated: Yes

Abstract

Background: Biology has entered the era of big data with the advent of high-throughput omics technologies. Biological databases provide public access to petabytes of data and information facilitating knowledge discovery. Over the years, sequence data of pathogens has seen a large increase in the number of records, given the relatively small genome size and their important role as infectious and symbiotic agents. Humans are host to numerous pathogenic diseases, such as that by viruses, many of which are responsible for high mortality and morbidity. The interaction between pathogens and humans over the evolutionary history has resulted in sharing of sequences, with important biological and evolutionary implications.