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New approach for understanding genome variations in KEGG.

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TLDR
This work has introduced a new approach where human gene variants are explicitly incorporated into what it calls ‘network variants’ in the recently released KEGG NETWORK database, which allows accumulation of knowledge about disease-related perturbed molecular networks caused not only by gene variants, but also by viruses and other pathogens, environmental factors and drugs.
Abstract
KEGG (Kyoto Encyclopedia of Genes and Genomes; https://www.kegg.jp/ or https://www.genome.jp/kegg/) is a reference knowledge base for biological interpretation of genome sequences and other high-throughput data. It is an integrated database consisting of three generic categories of systems information, genomic information and chemical information, and an additional human-specific category of health information. KEGG pathway maps, BRITE hierarchies and KEGG modules have been developed as generic molecular networks with KEGG Orthology nodes of functional orthologs so that KEGG pathway mapping and other procedures can be applied to any cellular organism. Unfortunately, however, this generic approach was inadequate for knowledge representation in the health information category, where variations of human genomes, especially disease-related variations, had to be considered. Thus, we have introduced a new approach where human gene variants are explicitly incorporated into what we call 'network variants' in the recently released KEGG NETWORK database. This allows accumulation of knowledge about disease-related perturbed molecular networks caused not only by gene variants, but also by viruses and other pathogens, environmental factors and drugs. We expect that KEGG NETWORK will become another reference knowledge base for the basic understanding of disease mechanisms and practical use in clinical sequencing and drug development.

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Citations
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g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update).

TL;DR: G:Profiler is now capable of analysing data from any organism, including vertebrates, plants, fungi, insects and parasites, and the 2019 update introduces an extensive technical rewrite making the services faster and more flexible.
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KEGG: integrating viruses and cellular organisms.

TL;DR: The K EGG pathway maps are now integrated with network variation maps in the NETWORK database, as well as with conserved functional units of KEGG modules and reaction modules in the MODULE database, and the KO database for functional orthologs continues to be improved.
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Toward understanding the origin and evolution of cellular organisms.

TL;DR: The KEGG resource that the team has been developing is a reference knowledge base for biological interpretation of genome sequences and other high‐throughput data, and is now one of the most utilized biological databases because of its practical values.
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Transcriptomic characteristics of bronchoalveolar lavage fluid and peripheral blood mononuclear cells in COVID-19 patients.

TL;DR: The results reveal distinct host inflammatory cytokine profiles to SARS-CoV-2 infection in patients, and highlight the association between COVID-19 pathogenesis and excessive cytokine release such as CCL2/MCP-1, CXCL10/IP-10, CCL3/MIP-1A, and CCL4/Mip1B.
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Protocol Update for large-scale genome and gene function analysis with the PANTHER classification system (v.14.0)

TL;DR: The authors provide an update to their 2013 protocol for using the PANTHER classification system, detailing how to analyze genome-wide experimental data with the newest version of PANTHER (v.14.0), with improvements in the areas of data quality, data coverage, statistical algorithms and user experience.
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TL;DR: This work has been supported by the Department of the Army and the National Institutes of Health, and the author acknowledges the support and encouragement of the National Cancer Institute.
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KEGG: new perspectives on genomes, pathways, diseases and drugs

TL;DR: The content has been expanded and the quality improved irrespective of whether or not the KOs appear in the three molecular network databases, and the newly introduced addendum category of the GENES database is a collection of individual proteins whose functions are experimentally characterized and from which an increasing number of KOs are defined.
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KEGG as a reference resource for gene and protein annotation

TL;DR: The KEGG GENES database now includes viruses, plasmids, and the addendum category for functionally characterized proteins that are not represented in complete genomes, and new automatic annotation servers, BlastKOalA and GhostKOALA, are made available utilizing the non-redundant pangenome data set generated from theGENES database.
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