title: A hybrid approach to gene ranking using gene relation networks derived from literature for the identification of disease gene markers.
abstract: For the identification of gene markers involved in diseases, microarray expression profiles have been widely used to prioritize genes. In this paper, we propose a novel approach to gene ranking that employs gene relation network derived from literature along with microarray expression scores to calculate ranking statistics of individual genes. In particular, the gene relation network is constructed from literature by applying syntactic analysis and co-occurrence method in a hybrid manner. For evaluation, the proposed method was tested with publicly available prostate cancer data. The result shows that our method is superior to other existing approaches.
authors.affiliation: Bio-Intelligence Mining Lab., College of IT Engineering, Kyungpook National University, 1370 Sankyuk-dong, Buk-gu, Daegu 702-701, Korea. shinmy@knu.ac.kr
authors.forename: Miyoung
authors.initials: M
authors.lastname: Shin
authors.forename: Hyungmin
authors.initials: H
authors.lastname: Lee
authors.forename: Munpyo
authors.initials: M
authors.lastname: Hong
mesh_terms: D000465:Algorithms; D004194:Disease / Q000235:genetics; D020869:Gene Expression Profiling / Q000379:methods*; D053263:Gene Regulatory Networks; D005819:Genetic Markers; D023281:Genomics / Q000379:methods*; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods
chemical_list: D005819:Genetic Markers