Literature DB >> 16280644

Integrating genetic and gene expression data to study the metabolic syndrome and diabetes in mice.

Thomas A Drake1, Eric E Schadt, Richard C Davis, Aldons J Lusis.   

Abstract

Increasingly, the mouse is becoming the standard model for mammalian physiology and disease. It can be genetically analyzed and manipulated with relative ease. Moreover, the endogenous genetic variation that exists among inbred mouse strains can be exploited to identify genetic control of complex physiologic processes involved in diabetes and the metabolic syndrome, among other conditions relevant to human disease. Recent advances in genetics and gene expression technology have greatly increased the knowledge to be derived from this approach when applied to traditional genetic studies.

Entities:  

Mesh:

Year:  2005        PMID: 16280644     DOI: 10.1097/01.mjt.0000178775.39149.64

Source DB:  PubMed          Journal:  Am J Ther        ISSN: 1075-2765            Impact factor:   2.688


  9 in total

1.  Identification of quantitative trait loci underlying proteome variation in human lymphoblastoid cells.

Authors:  Nikhil Garge; Huaqin Pan; Megan D Rowland; Benjamin J Cargile; Xinxin Zhang; Phillip C Cooley; Grier P Page; Maureen K Bunger
Journal:  Mol Cell Proteomics       Date:  2010-02-23       Impact factor: 5.911

Review 2.  Genomic resources for dissecting the role of non-protein coding variation in gene-environment interactions.

Authors:  Daniel Levings; Kirsten E Shaw; Sarah E Lacher
Journal:  Toxicology       Date:  2020-05-22       Impact factor: 4.221

Review 3.  Toxicogenetics: population-based testing of drug and chemical safety in mouse models.

Authors:  Ivan Rusyn; Daniel M Gatti; Timothy Wiltshire; Timothy Wilshire; Steven R Kleeberger; David W Threadgill
Journal:  Pharmacogenomics       Date:  2010-08       Impact factor: 2.533

4.  Post genome-wide association studies functional characterization of prostate cancer risk loci.

Authors:  Junfeng Jiang; Weirong Cui; Wanwipa Vongsangnak; Guang Hu; Bairong Shen
Journal:  BMC Genomics       Date:  2013-12-09       Impact factor: 3.969

5.  A systems genetics approach identifies CXCL14, ITGAX, and LPCAT2 as novel aggressive prostate cancer susceptibility genes.

Authors:  Kendra A Williams; Minnkyong Lee; Ying Hu; Jonathan Andreas; Shashank J Patel; Suiyuan Zhang; Peter Chines; Abdel Elkahloun; Settara Chandrasekharappa; J Silvio Gutkind; Alfredo A Molinolo; Nigel P S Crawford
Journal:  PLoS Genet       Date:  2014-11-20       Impact factor: 5.917

6.  Cross-phenotype association tests uncover genes mediating nutrient response in Drosophila.

Authors:  Christopher S Nelson; Jennifer N Beck; Kenneth A Wilson; Elijah R Pilcher; Pankaj Kapahi; Rachel B Brem
Journal:  BMC Genomics       Date:  2016-11-04       Impact factor: 3.969

7.  Sex specific gene regulation and expression QTLs in mouse macrophages from a strain intercross.

Authors:  Jeffrey M Bhasin; Enakshi Chakrabarti; Dao-Quan Peng; Aneesh Kulkarni; Xi Chen; Jonathan D Smith
Journal:  PLoS One       Date:  2008-01-16       Impact factor: 3.240

8.  Exon and junction microarrays detect widespread mouse strain- and sex-bias expression differences.

Authors:  Wan-Lin Su; Barmak Modrek; Debraj GuhaThakurta; Stephen Edwards; Jyoti K Shah; Amit V Kulkarni; Archie Russell; Eric E Schadt; Jason M Johnson; John C Castle
Journal:  BMC Genomics       Date:  2008-06-04       Impact factor: 3.969

9.  Biomarkers for combat-related PTSD: focus on molecular networks from high-dimensional data.

Authors:  Thomas C Neylan; Eric E Schadt; Rachel Yehuda
Journal:  Eur J Psychotraumatol       Date:  2014-08-14
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.