Integration of Heterogeneous Expression Data Sets Extends the Role of the Retinol Pathway in Diabetes and Insulin Resistance

DSpace/Manakin Repository

Integration of Heterogeneous Expression Data Sets Extends the Role of the Retinol Pathway in Diabetes and Insulin Resistance

Citable link to this page

. . . . . .

Title: Integration of Heterogeneous Expression Data Sets Extends the Role of the Retinol Pathway in Diabetes and Insulin Resistance
Author: Tebaldi, Toma; Lai, Weil R.; Kasif, Simon; Park, Peter J.; Kong, Sek Won Won; Kohane, Isaac Samuel

Note: Order does not necessarily reflect citation order of authors.

Citation: Park, Peter J., Sek Won Kong, Toma Tebaldi, Weil R. Lai, Simon Kasif, and Isaac S. Kohane. 2009. Integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance. Bioinformatics 25(23): 3121-3127.
Full Text & Related Files:
Abstract: Motivation: Type 2 diabetes is a chronic metabolic disease that involves both environmental and genetic factors. To understand the genetics of type 2 diabetes and insulin resistance, the DIabetes Genome Anatomy Project (DGAP) was launched to profile gene expression in a variety of related animal models and human subjects. We asked whether these heterogeneous models can be integrated to provide consistent and robust biological insights into the biology of insulin resistance. Results: We perform integrative analysis of the 16 DGAP data sets that span multiple tissues, conditions, array types, laboratories, species, genetic backgrounds and study designs. For each data set, we identify differentially expressed genes compared with control. Then, for the combined data, we rank genes according to the frequency with which they were found to be statistically significant across data sets. This analysis reveals RetSat as a widely shared component of mechanisms involved in insulin resistance and sensitivity and adds to the growing importance of the retinol pathway in diabetes, adipogenesis and insulin resistance. Top candidates obtained from our analysis have been confirmed in recent laboratory studies. Contact: Isaac_kohane@harvard.edu
Published Version: doi:10.1093/bioinformatics/btp559
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2778339/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4724756

Show full Dublin Core record

This item appears in the following Collection(s)

 
 

Search DASH


Advanced Search
 
 

Submitters