title: Degree-adjusted algorithm for prioritisation of candidate disease genes from gene expression and protein interactome.
abstract: Computational methods play an important role in the disease genes prioritisation by integrating many kinds of data sources such as gene expression, functional annotations and protein-protein interactions. However, the existing methods usually perform well in predicting highly linked genes, whereas they work quite poorly for loosely linked genes. Motivated by this observation, a degree-adjusted strategy is applied to improve the algorithm that was proposed earlier for the prediction of disease genes from gene expression and protein interactions. The authors also showed that the modified method is good at identifying loosely linked disease genes and the overall performance gets enhanced accordingly. This study suggests the importance of statistically adjusting the degree distribution bias in the background network for network-based modelling of complex diseases.
authors.affiliation: Department of Mathematics, Logistical Engineering University, Chongqing, People's Republic of China.
authors.forename: Yichuan
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Department of Mathematics, Logistical Engineering University, Chongqing, People's Republic of China.
authors.forename: Haiyang
authors.initials: H
authors.lastname: Fang
authors.affiliation: Department of Mathematics, Logistical Engineering University, Chongqing, People's Republic of China.
authors.forename: Tinghong
authors.initials: T
authors.lastname: Yang
authors.affiliation: Department of Mathematics, Logistical Engineering University, Chongqing, People's Republic of China.
authors.forename: Duzhi
authors.initials: D
authors.lastname: Wu
authors.affiliation: Department of Mathematics, Logistical Engineering University, Chongqing, People's Republic of China. zhaojanne@gmail.com.
authors.forename: Jing
authors.initials: J
authors.lastname: Zhao
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D030342:Genetic Diseases, Inborn / Q000235:genetics; D020022:Genetic Predisposition to Disease; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D025941:Protein Interaction Mapping / Q000379:methods*; D012372:ROC Curve