Methods for Mining Single Nucleotide Polymorphism Data of Complex Diseases

Author(s): Xiong Li*.

Journal Name: Current Bioinformatics

Volume 13 , Issue 4 , 2018

Graphical Abstract:


Abstract:

Background: A key goal of mining single nucleotide polymorphism data of complex diseases (CD) is to build models that provide fundamental insight into genetic variations of CD. Therefore, we can predict disease risk and clinical outcomes and ultimately understand the development and progress mechanism of CD. As the technologies of omics data generation and computer science, the reductionist paradigm of genome wide association study becomes less prevalent.

Conclusion: In this review, we summarize the different strategies for boosting the power of association study, which include data quality improvement, high-performance computing platform and advanced computational method. Using these complementary approaches, the fundamental mechanism of genomic variations affecting occurrence and development of CD may be uncovered.

Keywords: Complex diseases, epistasis, systems biology, cloud computing, data integration.

Rights & PermissionsPrintExport Cite as

Article Details

VOLUME: 13
ISSUE: 4
Year: 2018
Page: [367 - 372]
Pages: 6
DOI: 10.2174/1574893612666170619083537
Price: $58

Article Metrics

PDF: 5