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1.
Nucleic Acids Res ; 48(D1): D1093-D1103, 2020 01 08.
Article in English | MEDLINE | ID: mdl-31680153

ABSTRACT

Plant Reactome (https://plantreactome.gramene.org) is an open-source, comparative plant pathway knowledgebase of the Gramene project. It uses Oryza sativa (rice) as a reference species for manual curation of pathways and extends pathway knowledge to another 82 plant species via gene-orthology projection using the Reactome data model and framework. It currently hosts 298 reference pathways, including metabolic and transport pathways, transcriptional networks, hormone signaling pathways, and plant developmental processes. In addition to browsing plant pathways, users can upload and analyze their omics data, such as the gene-expression data, and overlay curated or experimental gene-gene interaction data to extend pathway knowledge. The curation team actively engages researchers and students on gene and pathway curation by offering workshops and online tutorials. The Plant Reactome supports, implements and collaborates with the wider community to make data and tools related to genes, genomes, and pathways Findable, Accessible, Interoperable and Re-usable (FAIR).


Subject(s)
Computational Biology/methods , Databases, Genetic , Genomics , Metabolomics , Plants/genetics , Plants/metabolism , Proteomics , Gene Regulatory Networks , Genomics/methods , Humans , Metabolic Networks and Pathways , Metabolomics/methods , Proteomics/methods , Signal Transduction , Web Browser
2.
Nucleic Acids Res ; 42(Database issue): D472-7, 2014 Jan.
Article in English | MEDLINE | ID: mdl-24243840

ABSTRACT

Reactome (http://www.reactome.org) is a manually curated open-source open-data resource of human pathways and reactions. The current version 46 describes 7088 human proteins (34% of the predicted human proteome), participating in 6744 reactions based on data extracted from 15 107 research publications with PubMed links. The Reactome Web site and analysis tool set have been completely redesigned to increase speed, flexibility and user friendliness. The data model has been extended to support annotation of disease processes due to infectious agents and to mutation.


Subject(s)
Databases, Protein , Proteins/metabolism , Disease , Humans , Internet , Knowledge Bases , Metabolic Networks and Pathways
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