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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/18849

Title: Translation of disease associated gene signatures across tissues
Authors: KASIM, Adetayo
SHKEDY, Ziv
LIN, Dan
VAN SANDEN, Suzy
CORTINAS ABRAHANTES, Jose
Goehlmann, Hinrich W. H.
BIJNENS, Luc
Yekutieli, Dani
Camilleri, Michael
Aerssens, Jeroen
TALLOEN, Willem
Issue Date: 2015
Publisher: INDERSCIENCE ENTERPRISES LTD
Citation: INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS, 11 (3), p. 301-313
Abstract: It has recently been shown that disease associated gene signatures can be identified by profiling tissue other than the disease related tissue. In this paper, we investigate gene signatures for Irritable Bowel Syndrome (IBS) using gene expression profiling of both disease related tissue (colon) and surrogate tissue (rectum). Gene specific joint ANOVA models were used to investigate differentially expressed genes between the IBS patients and the healthy controls taken into account both intra and inter tissue dependencies among expression levels of the same gene. Classification algorithms in combination with feature selection methods were used to investigate the predictive power of gene expression levels from the surrogate and the target tissues. We conclude based on the analyses that expression profiles of the colon and the rectum tissue could result in better predictive accuracy if the disease associated genes are known.
Notes: [Kasim, Adetayo] Univ Durham, Wolfson Res Inst Hlth & Wellbeing, Stockton On Tees TS17 6BH, England. [Shkedy, Ziv; Lin, Dan] Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, Diepenbeek, Belgium. [Van Sanden, Suzy; Goehlmann, Hinrich W. H.; Bijnens, Luc; Aerssens, Jeroen; Talloen, Willem] Janssen Pharmaceut NV, Beerse, Belgium. [Abrahantes, Jose Cortinas] European Food Safety Author, Parma, Italy. [Yekutieli, Dani] Tel Aviv Univ, Dept Stat & Operat Res, IL-69978 Tel Aviv, Israel. [Camilleri, Michael] Mayo Clin, Coll Med, Rochester, MN USA.
URI: http://hdl.handle.net/1942/18849
DOI: 10.1504/IJDMB.2015.067321
ISI #: 000352841700003
ISSN: 1748-5673
Category: A1
Type: Journal Contribution
Validation: ecoom, 2016
Appears in Collections: Research publications

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