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Computational Intelligence and Pattern Analysis in Biological Informatics by Jason T. Wang, Sanghamitra Bandyopadhyay, Ujjwal Maulik

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CHAPTER 14

TECHNIQUES FOR PRIORITIZATION OF CANDIDATE DISEASE GENES

JIEUN JEONG AND JAKE Y. CHEN

14.1 INTRODUCTION

Gene prioritization is a new approach for extending our knowledge about diseases and phenotypic information each gene encodes. We will review computational methods that have been described to date and attempt to identify which are most successful and what are the remaining challenges. The motivations and applications of this topic been well described in [1]. Therefore, we focus on how to enable a biologist to select the best existing method for a given application context. At the same time, we would like to identify remaining open research problems for practitioners in bioinformatics.

The general notion of gene prioritization assumes that one has a set of candidates and he wants to order the candidates from the most promising to the least promising one. A primary motivation for prioritization of candidate disease genes comes from the analysis of linkage regions that contain genetic elements of diseases. In this setting, the notion of a disease gene is unambiguous: a genetic element that confers disease susceptibility if its variants is present in the genome. For a particular disease phenotype, researchers often have a list of candidate genes usually genes located in a linkage interval associated with the disease. Finding the actual gene and candidate can be a subject of expensive experimental validations; however, once identified as real, these disease-associated ...

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