Computational approaches for disease gene identification
Date of Issue2014
School of Computer Engineering
Bioinformatics Research Centre
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.
DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications