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SNPs3D: Candidate gene and SNP selection for association studies
BACKGROUND: The relationship between disease susceptibility and genetic variation is complex, and many different types of data are relevant. We describe a web resource and database that provides and integrates as much information as possible on disease/gene relationships at the molecular level. DESC...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2006
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1435944/ https://www.ncbi.nlm.nih.gov/pubmed/16551372 http://dx.doi.org/10.1186/1471-2105-7-166 |
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author | Yue, Peng Melamud, Eugene Moult, John |
author_facet | Yue, Peng Melamud, Eugene Moult, John |
author_sort | Yue, Peng |
collection | PubMed |
description | BACKGROUND: The relationship between disease susceptibility and genetic variation is complex, and many different types of data are relevant. We describe a web resource and database that provides and integrates as much information as possible on disease/gene relationships at the molecular level. DESCRIPTION: The resource has three primary modules. One module identifies which genes are candidates for involvement in a specified disease. A second module provides information about the relationships between sets of candidate genes. The third module analyzes the likely impact of non-synonymous SNPs on protein function. Disease/candidate gene relationships and gene-gene relationships are derived from the literature using simple but effective text profiling. SNP/protein function relationships are derived by two methods, one using principles of protein structure and stability, the other based on sequence conservation. Entries for each gene include a number of links to other data, such as expression profiles, pathway context, mouse knockout information and papers. Gene-gene interactions are presented in an interactive graphical interface, providing rapid access to the underlying information, as well as convenient navigation through the network. Use of the resource is illustrated with aspects of the inflammatory response and hypertension. CONCLUSION: The combination of SNP impact analysis, a knowledge based network of gene relationships and candidate genes, and access to a wide range of data and literature allow a user to quickly assimilate available information, and so develop models of gene-pathway-disease interaction. |
format | Text |
id | pubmed-1435944 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-14359442006-04-14 SNPs3D: Candidate gene and SNP selection for association studies Yue, Peng Melamud, Eugene Moult, John BMC Bioinformatics Database BACKGROUND: The relationship between disease susceptibility and genetic variation is complex, and many different types of data are relevant. We describe a web resource and database that provides and integrates as much information as possible on disease/gene relationships at the molecular level. DESCRIPTION: The resource has three primary modules. One module identifies which genes are candidates for involvement in a specified disease. A second module provides information about the relationships between sets of candidate genes. The third module analyzes the likely impact of non-synonymous SNPs on protein function. Disease/candidate gene relationships and gene-gene relationships are derived from the literature using simple but effective text profiling. SNP/protein function relationships are derived by two methods, one using principles of protein structure and stability, the other based on sequence conservation. Entries for each gene include a number of links to other data, such as expression profiles, pathway context, mouse knockout information and papers. Gene-gene interactions are presented in an interactive graphical interface, providing rapid access to the underlying information, as well as convenient navigation through the network. Use of the resource is illustrated with aspects of the inflammatory response and hypertension. CONCLUSION: The combination of SNP impact analysis, a knowledge based network of gene relationships and candidate genes, and access to a wide range of data and literature allow a user to quickly assimilate available information, and so develop models of gene-pathway-disease interaction. BioMed Central 2006-03-22 /pmc/articles/PMC1435944/ /pubmed/16551372 http://dx.doi.org/10.1186/1471-2105-7-166 Text en Copyright © 2006 Yue et al; licensee BioMed Central Ltd. |
spellingShingle | Database Yue, Peng Melamud, Eugene Moult, John SNPs3D: Candidate gene and SNP selection for association studies |
title | SNPs3D: Candidate gene and SNP selection for association studies |
title_full | SNPs3D: Candidate gene and SNP selection for association studies |
title_fullStr | SNPs3D: Candidate gene and SNP selection for association studies |
title_full_unstemmed | SNPs3D: Candidate gene and SNP selection for association studies |
title_short | SNPs3D: Candidate gene and SNP selection for association studies |
title_sort | snps3d: candidate gene and snp selection for association studies |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1435944/ https://www.ncbi.nlm.nih.gov/pubmed/16551372 http://dx.doi.org/10.1186/1471-2105-7-166 |
work_keys_str_mv | AT yuepeng snps3dcandidategeneandsnpselectionforassociationstudies AT melamudeugene snps3dcandidategeneandsnpselectionforassociationstudies AT moultjohn snps3dcandidategeneandsnpselectionforassociationstudies |