title: Identifying module biomarker in type 2 diabetes mellitus by discriminative area of functional activity.
abstract: BACKGROUND
  Identifying diagnosis and prognosis biomarkers from expression profiling data is of great significance for achieving personalized medicine and designing therapeutic strategy in complex diseases. However, the reproducibility of identified biomarkers across tissues and experiments is still a challenge for this issue.
  
  
  RESULTS
  We propose a strategy based on discriminative area of module activities to identify gene biomarkers which interconnect as a subnetwork or module by integrating gene expression data and protein-protein interactions. Then, we implement the procedure in T2DM as a case study and identify a module biomarker with 32 genes from mRNA expression data in skeletal muscle for T2DM. This module biomarker is enriched with known causal genes and related functions of T2DM. Further analysis shows that the module biomarker is of superior performance in classification, and has consistently high accuracies across tissues and experiments.
  
  
  CONCLUSIONS
  The proposed approach can efficiently identify robust and functionally meaningful module biomarkers in T2DM, and could be employed in biomarker discovery of other complex diseases characterized by expression profiles.
authors.affiliation: School of Computer Science and Technology, Xidian University, Xi'an, 710000, China. zxd841@163.com.|Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China. zxd841@163.com.
authors.forename: Xindong
authors.initials: X
authors.lastname: Zhang
authors.affiliation: School of Computer Science and Technology, Xidian University, Xi'an, 710000, China. lgao@mail.xidian.edu.cn.|Institute of Industrial Science, University of Tokyo, Tokyo, 153-8505, Japan. lgao@mail.xidian.edu.cn.
authors.forename: Lin
authors.initials: L
authors.lastname: Gao
authors.affiliation: Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Shandong, 250061, China. zpliu@sdu.edu.cn.
authors.forename: Zhi-Ping
authors.initials: ZP
authors.lastname: Liu
authors.affiliation: Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China. lnchen@sibs.ac.cn.|Institute of Industrial Science, University of Tokyo, Tokyo, 153-8505, Japan. lnchen@sibs.ac.cn.|School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China. lnchen@sibs.ac.cn.
authors.forename: Luonan
authors.initials: L
authors.lastname: Chen
mesh_terms: D015415:Biomarkers / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics / Q000378:metabolism*; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D006801:Humans; D018482:Muscle, Skeletal / Q000378:metabolism; D025941:Protein Interaction Mapping
chemical_list: D015415:Biomarkers