Guan Lab

Department of Computational Medicine & Bioinformatics
Thu, 07/30/2015 - 12:27 -- gyuanfan
TitleGenes Caught In Flagranti: Integrating Renal Transcriptional Profiles With Genotypes and Phenotypes.
Publication TypeJournal Article
Year of Publication2015
AuthorsGuan Y, Martini S, Mariani LH
JournalSemin Nephrol
Volume35
Issue3
Pagination237-44
Date Published2015 May
ISSN1558-4488
Abstract

In the past decade, population genetics has gained tremendous success in identifying genetic variations that are statistically relevant to renal diseases and kidney function. However, it is challenging to interpret the functional relevance of the genetic variations found by population genetics studies. In this review, we discuss studies that integrate multiple levels of data, especially transcriptome profiles and phenotype data, to assign functional roles of genetic variations involved in kidney function. Furthermore, we introduce state-of-the-art machine learning algorithms, Bayesian networks, support vector machines, and Gaussian process regression, which have been applied successfully to integrating genetic, regulatory, and clinical information to predict clinical outcomes. These methods are likely to be deployed successfully in the nephrology field in the near future.

DOI10.1016/j.semnephrol.2015.04.003
Alternate JournalSemin. Nephrol.
PubMed ID26215861