Protocol

Disease Gene Identification

Volume 700 of the series Methods in Molecular Biology pp 241-259

Date:

Integrative Systems Biology Approaches to Identify and Prioritize Disease and Drug Candidate Genes

  • Vivek KaimalAffiliated withDivision of Biomedical Informatics, Cincinnati Children’s Hospital Medical CenterDepartment of Biomedical Engineering, University of Cincinnati
  • , Divya SardanaAffiliated withDepartment of Computer Science, College of Engineering, University of Cincinnati
  • , Eric E. BardesAffiliated withDivision of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
  • , Ranga Chandra GudivadaAffiliated withDivision of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
  • , Jing ChenAffiliated withDepartment of Environmental Health, University of Cincinnati
  • , Anil G. JeggaAffiliated withDivision of Biomedical Informatics, Cincinnati Children’s Hospital Medical CenterDepartment of Biomedical Engineering, University of CincinnatiDepartment of Pediatrics, College of Medicine, University of Cincinnati Email author 

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Abstract

Although a number of computational approaches have been developed to integrate data from multiple sources for the purpose of predicting or prioritizing candidate disease genes, relatively few of them focus on identifying or ranking drug targets. To address this deficit, we have developed an approach to specifically identify and prioritize disease and drug candidate genes. In this chapter, we demonstrate the applicability of integrative systems-biology-based approaches to identify potential drug targets and candidate genes by employing information extracted from public databases. We illustrate the method in detail using examples of two neurodegenerative diseases (Alzheimer’s and Parkinson’s) and one neuropsychiatric disease (Schizophrenia).

Key words

Candidate gene prioritization Disease gene ranking Drug target ranking Integrative genomics Systems biology Alzheimer’s disease Parkinson’s disease Schizophrenia