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Medicine and Health Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

Genetics and Genomics

University of Kentucky

Series

2019

Gene Expression Regulation

Articles 1 - 2 of 2

Full-Text Articles in Medicine and Health Sciences

An Integrative Cross-Omics Analysis Of Dna Methylation Sites Of Glucose And Insulin Homeostasis, Jun Liu, Elena Carnero-Montoro, Jenny Van Dongen, Samantha Lent, Ivana Nedeljkovic, Symen Ligthart, Pei-Chien Tsai, Tiphaine C. Martin, Pooja R. Mandaviya, Rick Jansen, Marjolein J. Peters, Liesbeth Duijts, Vincent W. V. Jaddoe, Henning Tiemeier, Janine F. Felix, Gonneke Willemsen, Eco J. C. De Geus, Audrey Y. Chu, Daniel Levy, Shih-Jen Hwang, Jan Bressler, Rahul Gondalia, Elias L. Salfati, Christian Herder, Bertha A. Hidalgo, Toshiko Tanaka, Ann Zenobia Moore, Rozenn N. Lemaitre, Min A. Jhun, Jennifer A. Smith, Donna K. Arnett Jun 2019

An Integrative Cross-Omics Analysis Of Dna Methylation Sites Of Glucose And Insulin Homeostasis, Jun Liu, Elena Carnero-Montoro, Jenny Van Dongen, Samantha Lent, Ivana Nedeljkovic, Symen Ligthart, Pei-Chien Tsai, Tiphaine C. Martin, Pooja R. Mandaviya, Rick Jansen, Marjolein J. Peters, Liesbeth Duijts, Vincent W. V. Jaddoe, Henning Tiemeier, Janine F. Felix, Gonneke Willemsen, Eco J. C. De Geus, Audrey Y. Chu, Daniel Levy, Shih-Jen Hwang, Jan Bressler, Rahul Gondalia, Elias L. Salfati, Christian Herder, Bertha A. Hidalgo, Toshiko Tanaka, Ann Zenobia Moore, Rozenn N. Lemaitre, Min A. Jhun, Jennifer A. Smith, Donna K. Arnett

Epidemiology and Environmental Health Faculty Publications

Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential methylation in the early phases of T2D pathology by a blood-based epigenome-wide association study of 4808 non-diabetic Europeans in the discovery phase and 11,750 individuals in the replication. We identify CpGs in LETM1, RBM20, IRS2, MAN2A2 and the 1q25.3 region associated with fasting insulin, and in FCRL6, SLAMF1, APOBEC3H and the 15q26.1 region with fasting glucose. In silico cross-omics analyses highlight the role of differential methylation …


Incorporating Pathway Information Into Feature Selection Towards Better Performed Gene Signatures, Suyan Tian, Chi Wang, Bing Wang Apr 2019

Incorporating Pathway Information Into Feature Selection Towards Better Performed Gene Signatures, Suyan Tian, Chi Wang, Bing Wang

Biostatistics Faculty Publications

To analyze gene expression data with sophisticated grouping structures and to extract hidden patterns from such data, feature selection is of critical importance. It is well known that genes do not function in isolation but rather work together within various metabolic, regulatory, and signaling pathways. If the biological knowledge contained within these pathways is taken into account, the resulting method is a pathway-based algorithm. Studies have demonstrated that a pathway-based method usually outperforms its gene-based counterpart in which no biological knowledge is considered. In this article, a pathway-based feature selection is firstly divided into three major categories, namely, pathway-level selection, …