METU-SNP: An Integrated Software System for SNPComplex Disease Association Analysis

Recently, there has been increasing research to discover genomic biomarkers, haplotypes, and potentially other variables that together contribute to the development of diseases. Single Nucleotide Polymorphisms (SNPs) are the most common form of genomic variations and they can represent an individual...

Full description

Bibliographic Details
Main Authors: Üstünkar Gürkan, Son Yeşim Aydın
Format: Article
Language:English
Published: De Gruyter 2011-06-01
Series:Journal of Integrative Bioinformatics
Online Access:https://doi.org/10.1515/jib-2011-187
id doaj-4263b53df2cc43bfaf7cf20a082daaea
record_format Article
spelling doaj-4263b53df2cc43bfaf7cf20a082daaea2021-09-06T19:40:31ZengDe GruyterJournal of Integrative Bioinformatics1613-45162011-06-018220422110.1515/jib-2011-187biecoll-jib-2011-187METU-SNP: An Integrated Software System for SNPComplex Disease Association AnalysisÜstünkar Gürkan0Son Yeşim Aydın1METU, Informatics Institute, Department of Information Systems, 06531, Ankara, Turkey TurkeyMETU, Informatics Institute, Department of Health Informatics, 06531, Ankara, Turkey TurkeyRecently, there has been increasing research to discover genomic biomarkers, haplotypes, and potentially other variables that together contribute to the development of diseases. Single Nucleotide Polymorphisms (SNPs) are the most common form of genomic variations and they can represent an individual’s genetic variability in greatest detail. Genome-wide association studies (GWAS) of SNPs, high-dimensional case-control studies, are among the most promising approaches for identifying disease causing variants. METU-SNP software is a Java based integrated desktop application specifically designed for the prioritization of SNP biomarkers and the discovery of genes and pathways related to diseases via analysis of the GWAS case-control data. Outputs of METU-SNP can easily be utilized for the downstream biomarkers research to allow the prediction and the diagnosis of diseases and other personalized medical approaches. Here, we introduce and describe the system functionality and architecture of the METU-SNP. We believe that the METU-SNP will help researchers with the reliable identification of SNPs that are involved in the etiology of complex diseases, ultimately supporting the development of personalized medicine approaches and targeted drug discoverieshttps://doi.org/10.1515/jib-2011-187
collection DOAJ
language English
format Article
sources DOAJ
author Üstünkar Gürkan
Son Yeşim Aydın
spellingShingle Üstünkar Gürkan
Son Yeşim Aydın
METU-SNP: An Integrated Software System for SNPComplex Disease Association Analysis
Journal of Integrative Bioinformatics
author_facet Üstünkar Gürkan
Son Yeşim Aydın
author_sort Üstünkar Gürkan
title METU-SNP: An Integrated Software System for SNPComplex Disease Association Analysis
title_short METU-SNP: An Integrated Software System for SNPComplex Disease Association Analysis
title_full METU-SNP: An Integrated Software System for SNPComplex Disease Association Analysis
title_fullStr METU-SNP: An Integrated Software System for SNPComplex Disease Association Analysis
title_full_unstemmed METU-SNP: An Integrated Software System for SNPComplex Disease Association Analysis
title_sort metu-snp: an integrated software system for snpcomplex disease association analysis
publisher De Gruyter
series Journal of Integrative Bioinformatics
issn 1613-4516
publishDate 2011-06-01
description Recently, there has been increasing research to discover genomic biomarkers, haplotypes, and potentially other variables that together contribute to the development of diseases. Single Nucleotide Polymorphisms (SNPs) are the most common form of genomic variations and they can represent an individual’s genetic variability in greatest detail. Genome-wide association studies (GWAS) of SNPs, high-dimensional case-control studies, are among the most promising approaches for identifying disease causing variants. METU-SNP software is a Java based integrated desktop application specifically designed for the prioritization of SNP biomarkers and the discovery of genes and pathways related to diseases via analysis of the GWAS case-control data. Outputs of METU-SNP can easily be utilized for the downstream biomarkers research to allow the prediction and the diagnosis of diseases and other personalized medical approaches. Here, we introduce and describe the system functionality and architecture of the METU-SNP. We believe that the METU-SNP will help researchers with the reliable identification of SNPs that are involved in the etiology of complex diseases, ultimately supporting the development of personalized medicine approaches and targeted drug discoveries
url https://doi.org/10.1515/jib-2011-187
work_keys_str_mv AT ustunkargurkan metusnpanintegratedsoftwaresystemforsnpcomplexdiseaseassociationanalysis
AT sonyesimaydın metusnpanintegratedsoftwaresystemforsnpcomplexdiseaseassociationanalysis
_version_ 1717768345014501376