Abstract
BackgroundTo understand how stroke risk factors mechanistically contribute to stroke, the genetic components regulating each risk factor need to be integrated and evaluated with respect to biological function and through pathway-based algorithms. This resource will provide information to researchers studying the molecular and genetic causes of stroke in terms of genomic variants, genes, and pathways.MethodsReported genetic variants, gene structure, phenotypes, and literature information regarding stroke were collected and extracted from publicly available databases describing variants, genome, proteome, functional annotation, and disease subtypes. Stroke related candidate pathways and etiologic genes that participate significantly in risk were analyzed in terms of canonical pathways in public biological pathway databases. These efforts resulted in a relational database of genetic signals of cerebral stroke, SigCS base, which implements an effective web retrieval system.ResultsThe current version of SigCS base documents 1943 non-redundant genes with 11472 genetic variants and 165 non-redundant pathways. The web retrieval system of SigCS base consists of two principal search flows, including: 1) a gene-based variant search using gene table browsing or a keyword search, and, 2) a pathway-based variant search using pathway table browsing. SigCS base is freely accessible at http://sysbio.kribb.re.kr/sigcs.ConclusionsSigCS base is an effective tool that can assist researchers in the identification of the genetic factors associated with stroke by utilizing existing literature information, selecting candidate genes and variants for experimental studies, and examining the pathways that contribute to the pathophysiological mechanisms of stroke.
Highlights
Stroke is a heterogeneous complex disease that results from the interaction between genetic and environmental risk factors and has many well-established etiologies [1,2,3,4,5]
Data source and processing Online Mendelian Inheritance in Man (OMIM) [15] and Universal Protein Resource (UniProt) [16] were used to retrieve information on stroke- and etiology-related genetic variants; dbSNP [17] for SNP information; UCSC genome [18] for gene structure information, including transcript, exon/intron, coding region, and functional element data on SNPs; HUGO Gene Nomenclature Committee (HGNC) database [19] for standard gene names; Molecular Signatures Database (MSigDB) [20] for pathway and functional gene set information; and OMIM for literature information and PubMed links as raw data sources
SigCS base is an effective user-friendly tool designed to assist researchers in the identification of the molecular and genetic factors associated with stroke
Summary
Stroke is a heterogeneous complex disease that results from the interaction between genetic and environmental risk factors and has many well-established etiologies [1,2,3,4,5]. To understand how stroke risk factors mechanistically contribute to stroke, the genetic components regulating each risk factor need to be integrated and evaluated with respect to biological function and through pathway-based algorithms. This resource will provide information to researchers studying the molecular and genetic causes of stroke in terms of genomic variants, genes, and pathways
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