KEGG Mark-up Language
How to cite this record FAIRsharing.org: KGML; KEGG Mark-up Language; DOI: https://doi.org/10.25504/FAIRsharing.h6c48k; Last edited: Jan. 8, 2019, 1:37 p.m.; Last accessed: Nov 27 2020 8:23 p.m.
Record updated: March 15, 2018, 10:13 a.m. by The FAIRsharing Team.
Edits to 'https://fairsharing.org/FAIRsharing.h6c48k' by 'The FAIRsharing Team' at 10:13, 15 Mar 2018 (approved): 'miriam_url' has been modified: Before: None After:
Edits to 'https://fairsharing.org/FAIRsharing.h6c48k' by 'The FAIRsharing Team' at 08:53, 24 Oct 2016 (approved): 'description' has been modified: Before: "KEGG Mark-up Language" is a standard, specialising in the fields described under "scope and data types", below. Until this entry is claimed, more information on this project can be found at http://www.genome.jp/kegg/xml/. This text was generated automatically. If you work on the project responsible for "KEGG Mark-up Language" then please consider helping us by claiming this record and updating it appropriately. After: The KEGG Markup Language (KGML) is an exchange format of the KEGG pathway maps, which is converted from internally used KGML+ (KGML+SVG) format. KGML enables automatic drawing of KEGG pathways and provides facilities for computational analysis and modeling of gene/protein networks and chemical networks.
No XSD schemas defined
Conditions of Use
REST Web Services
No guidelines defined
No semantic standards defined
Models and Formats
No identifier schema standards defined
No metrics standards defined
iPAVS provides a collection of highly-structured manually curated human pathway data, it also integrates biological pathway information from several public databases and provides several tools to manipulate, filter, browse, search, analyze, visualize and compare the integrated pathway resources.
Genome-wide Integrated Analysis of gene Networks in Tissues 2.0
GIANT2 (Genome-wide Integrated Analysis of gene Networks in Tissues) is an interactive web server that enables biomedical researchers to analyze their proteins and pathways of interest and generate hypotheses in the context of genome-scale functional maps of human tissues. With GIANT2, researchers can explore predicted tissue-specific functional roles of genes and reveal changes in those roles across tissues, all through interactive multi-network visualizations and analyses.
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