title: Computational disease gene prioritization: an appraisal.
abstract: Bioinformatics aids in the understanding of the biological processes of living beings and the genetic architecture of human diseases. The discovery of disease-related genes improves the diagnosis and therapy design for the disease. To save the cost and time involved in the experimental verification of the candidate genes, computational methods are employed for ranking the genes according to their likelihood of being associated with the disease. Only top-ranked genes are then verified experimentally. A variety of methods have been conceived by the researchers for the prioritization of the disease candidate genes, which differ in the data source being used or the scoring function used for ranking the genes. A review of various aspects of computational disease gene prioritization and its research issues is presented in this article. The aspects covered are gene prioritization process, data sources used, types of prioritization methods, and performance assessment methods. This article provides a brief overview and acts as a quick guide for disease gene prioritization.
authors.affiliation: 1 Punjabi University Regional Centre For IT and Management , Mohali, Punjab, India .
authors.forename: Nivit
authors.initials: N
authors.lastname: Gill
authors.forename: Shailendra
authors.initials: S
authors.lastname: Singh
authors.forename: Trilok C
authors.initials: TC
authors.lastname: Aseri
mesh_terms: D019295:Computational Biology / Q000379:methods*; D020022:Genetic Predisposition to Disease; D006801:Humans; D008957:Models, Genetic; D017422:Sequence Analysis, DNA / Q000379:methods*
keywords: candidate gene prioritization; disease gene; gene ranking; network analysis method; similarity profiling method; text mining method