title: Integrative decomposition procedure and Kappa statistics for the distinguished single molecular network construction and analysis.
abstract: Our method concentrates on and constructs the distinguished single gene network. An integrated method was proposed based on linear programming and a decomposition procedure with integrated analysis of the significant function cluster using Kappa statistics and fuzzy heuristic clustering. We tested this method to identify ATF2 regulatory network module using data of 45 samples from the same GEO dataset. The results demonstrate the effectiveness of such integrated way in terms of developing novel prognostic markers and therapeutic targets.
authors.affiliation: Biomedical Center, School of Electronics Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China. wanglin98@tsinghua.org.cn
authors.forename: Lin
authors.initials: L
authors.lastname: Wang
authors.forename: Ying
authors.initials: Y
authors.lastname: Sun
authors.forename: Minghu
authors.initials: M
authors.lastname: Jiang
authors.forename: Xiguang
authors.initials: X
authors.lastname: Zheng
mesh_terms: D051698:Activating Transcription Factor 2 / Q000235:genetics / Q000502:physiology; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D017143:Fuzzy Logic; D053263:Gene Regulatory Networks; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis
chemical_list: C497105:ATF2 protein, human; D051698:Activating Transcription Factor 2