title: Systematic discovery of functional modules and context-specific functional annotation of human genome.
abstract: BACKGROUND
  The rapid accumulation of microarray datasets provides unique opportunities to perform systematic functional characterization of the human genome. We designed a graph-based approach to integrate cross-platform microarray data, and extract recurrent expression patterns. A series of microarray datasets can be modeled as a series of co-expression networks, in which we search for frequently occurring network patterns. The integrative approach provides three major advantages over the commonly used microarray analysis methods: (1) enhance signal to noise separation (2) identify functionally related genes without co-expression and (3) provide a way to predict gene functions in a context-specific way.
  
  
  RESULTS
  We integrate 65 human microarray datasets, comprising 1105 experiments and over 11 million expression measurements. We develop a data mining procedure based on frequent itemset mining and biclustering to systematically discover network patterns that recur in at least five datasets. This resulted in 143,401 potential functional modules. Subsequently, we design a network topology statistic based on graph random walk that effectively captures characteristics of a gene's local functional environment. Function annotations based on this statistic are then subject to the assessment using the random forest method, combining six other attributes of the network modules. We assign 1126 functions to 895 genes, 779 known and 116 unknown, with a validation accuracy of 70%. Among our assignments, 20% genes are assigned with multiple functions based on different network environments.
  
  
  BACKGROUND
  http://zhoulab.usc.edu/ContextAnnotation.
authors.affiliation: Molecuolar and Computational Biology, University of Southern California, Los Angeles, CA, USA.
authors.forename: Yu
authors.initials: Y
authors.lastname: Huang
authors.forename: Haifeng
authors.initials: H
authors.lastname: Li
authors.forename: Haiyan
authors.initials: H
authors.lastname: Hu
authors.forename: Xifeng
authors.initials: X
authors.lastname: Yan
authors.forename: Michael S
authors.initials: MS
authors.lastname: Waterman
authors.forename: Haiyan
authors.initials: H
authors.lastname: Huang
authors.forename: Xianghong Jasmine
authors.initials: XJ
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D002874:Chromosome Mapping / Q000379:methods*; D015870:Gene Expression / Q000235:genetics*; D020869:Gene Expression Profiling / Q000379:methods*; D015894:Genome, Human / Q000235:genetics*; D006801:Humans; D020543:Proteome / Q000235:genetics*; D015398:Signal Transduction / Q000235:genetics*
chemical_list: D020543:Proteome