Original Research ARTICLE
Multi-level comparative framework based on gene pair-wise expression across three insulin target tissues for type 2 diabetes
- 1Ludong University, School of Mathematics and Information Science, Yantai University, China
- 2Yantaishan Hospital, China
- 3Chinese Academy of Sciences, Academy of Mathematics and Systems Science (CAS), China
- 4Chinese Academy of Sciences, Center for Excellence in Animal Evolution and Genetics, Kunming Institute of Zoology (CAS), China
Type 2 diabetes (T2D) is known as a disease mainly caused by gene alterations characterized by insulin resistance, thus the insulin-responsive tissues are of great interests for T2D study. It’s in pressing need to systematically investigate commonalities and specificities of T2D among multiple tissues. Here we establish a multi-level comparative framework across three insulin target tissues (white adipose, skeletal muscle, and liver) to provide a better understanding of T2D. Starting from the ranks of gene expression, we construct the ‘disease network’ through detecting diverse interactions to provide a well-characterization for disease affected tissues. Then, we apply random walk with restarts algorithm to the disease network to prioritize its nodes and edges according to their association with T2D. Finally, we identified a merged core module by combining the clustering coefficient and Jaccard index, which can provide elaborate and visible illumination about the common and specific features for different tissues at network level. Taken together, our network-, gene-, and module-level characterization across different tissues of T2D hold the promise to provide a broader and deeper understanding for T2D mechanism.
Keywords: type 2 diabetes, gene pair-wise expression, Dysfunctional interactions, multi-level analysis, random walk with restart
Received: 24 Jan 2019;
Accepted: 06 Mar 2019.
Edited by:Quan Zou, University of Electronic Science and Technology of China, China
Reviewed by:Zhen Tian, Zhengzhou University, China
Tun-Wen Pai, National Taipei University of Technology, Taiwan
Copyright: © 2019 Sun, Sun and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Dr. Shaoyan Sun, School of Mathematics and Information Science, Yantai University, Ludong University, Yantai, China, email@example.com
Prof. Yong Wang, Academy of Mathematics and Systems Science (CAS), Chinese Academy of Sciences, Beijing, 100190, Beijing Municipality, China, firstname.lastname@example.org