ArticleProtein science : a publication of the Protein Society2023
KEGG tools for classification and analysis of viral proteins.
Article in Protein science : a publication of the Protein Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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35 citing papers in PubMed, 49 citations in OpenAlex.
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
The KEGG database and analysis tools (https://www.kegg.jp) have been developed mostly for understanding genes and genomes of cellular organisms. The KO (KEGG Orthology) dataset, which is a collection of functional orthologs, plays the role of linking genes in the genome to pathways and other molecular networks, enabling KEGG mapping to uncover hidden features in the genome. Although viruses were part of KEGG for some time, they were not fully integrated in the KEGG analysis tools, because the KO assignment rate is very low for virus genes. To supplement KOs a new dataset named virus ortholog clusters (VOCs) is computationally generated, covering 90% of viral proteins in KEGG. VOCs can be used, in place of KOs, for taxonomy mapping to uncover relationships of sequence similarity groups and taxonomic groups and for identifying conserved gene orders in virus genomes. Furthermore, selected VOCs are used to define tentative KOs for characterizing protein functions. Here an overview of KEGG tools is presented focusing on these extensions for viral protein analysis.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.