Gentrepid: a candidate gene prediction webserver
BackgroundThe identification of genes responsible for human disease enables an understanding of disease mechanisms and is essential for the development of diagnostics and therapeutics. Genetic studies can successfully identify genomic regions linked to a particular disease phenotype. Taking the next step of isolating the disease-causing gene can be difficult.For linkage analysis, genomic regions are often large,particularly for complex diseases. Genome-wide association (GWA) studies have greater power to detect genetic variants that confer modest disease risks than linkage analysis does, but even these may identify hundreds of SNPs. Currently, published GWA studies list only the 20-50 most-significant SNPs and their neighbouring genes (the mostsignificant SNPs approach), while paying little attention to the rest. A system that predicts and prioritizes candidates would be a great boon.
Jason Y Liu Guanglan Guo Diane Fatkin Merridee A Wouters Erdahl T Teber Richard A George Sara Ballouz Chi NI Pang Boer Xu Naresh P Bains Duncan B Sparrow Robin Otway
Victor Chang Cardiac Research Institute, NSW, Australia Victor Chang Cardiac Research Institute, NSW, Australia School of Medical Sciences, University of Ne
国际会议
The 7th Asia-Pacific Bioinformatics Conference(第七届亚太生物信息学大会)
北京
英文
911
2009-01-01（万方平台首次上网日期，不代表论文的发表时间）