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Journal of Integrative Bioinformatics

Editor-in-Chief: Schreiber, Falk / Hofestädt, Ralf

Managing Editor: Sommer, Björn

Hrsg. v. Baumbach, Jan / Chen, Ming / Orlov, Yuriy / Allmer, Jens

Wissenschaftlicher Beirat: Giorgetti, Alejandro / Harrison, Andrew / Kochetov, Aleksey / Krüger, Jens / Ma, Qi / Matsuno, Hiroshi / Mitra, Chanchal K. / Pauling, Josch K. / Rawlings, Chris / Fdez-Riverola, Florentino / Romano, Paolo / Röttger, Richard / Shoshi, Alban / Soares, Siomar de Castro / Taubert, Jan / Tauch, Andreas / Yousef, Malik / Weise, Stephan / Hassani-Pak, Keywan


CiteScore 2018: 0.90

SCImago Journal Rank (SJR) 2018: 0.315

Open Access
Online
ISSN
1613-4516
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Band 8, Heft 2

Hefte

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

Gürkan Üstünkar
  • Korrespondenzautor
  • METU, Informatics Institute, Department of Information Systems, 06531, Ankara, Turkey Turkey
  • Gennovate Corporation, 06531, Ankara, Turkey
  • E-Mail
  • Weitere Artikel des Autors:
  • De Gruyter OnlineGoogle Scholar
/ Yeşim Aydın Son
  • METU, Informatics Institute, Department of Health Informatics, 06531, Ankara, Turkey Turkey
  • METU, Bioinformatics Graduate Program, 06531, Ankara, Turkey
  • Weitere Artikel des Autors:
  • De Gruyter OnlineGoogle Scholar
Online erschienen: 18.10.2016 | DOI: https://doi.org/10.1515/jib-2011-187

Summary

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

Artikelinformationen

Online erschienen: 18.10.2016

Erschienen im Druck: 01.06.2011


Quellenangabe: Journal of Integrative Bioinformatics, Band 8, Heft 2, Seiten 204–221, ISSN (Online) 1613-4516, DOI: https://doi.org/10.1515/jib-2011-187.

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© 2011 The Author(s). Published by Journal of Integrative Bioinformatics.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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