Computational approaches for disease gene identification

Identifying disease genes from the human genome is a crucial but challenging task in the area of bioinformatics research and medical health. In wet-lab experiments, disease genes are identified using mutation analysis, which is very expensive and labor intensive. In this thesis, we proposed novel co...

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Bibliographic Details
Main Author: Yang, Peng
Other Authors: Ng See-Kiong
Format: Theses and Dissertations
Language:English
Published: 2014
Subjects:
Online Access:https://hdl.handle.net/10356/59238
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Institution: Nanyang Technological University
Language: English
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Summary:Identifying disease genes from the human genome is a crucial but challenging task in the area of bioinformatics research and medical health. In wet-lab experiments, disease genes are identified using mutation analysis, which is very expensive and labor intensive. In this thesis, we proposed novel computational approaches to prioritize and identify disease genes. The experimental results show that our work is more robust and accurate than other state-of-the-the-art techniques for disease gene identification.