Towards applying associative classifier for genetic variants

Authors:
Sofianita Mutalib;Shuzlina Abdul Rahman;Azlinah Mohamed
Affiliations:
Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia;Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia;Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia
Venue:
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part I
Year:
2012

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Abstract

With the availability of biological data and the power of sharing, it produces many opportunities for computer scientists to perform researches in bioinformatics. Generally the researches propose methods for different tasks, mainly to develop algorithms in diagnosing and identification of diseases. One of the primary studies that relevant to health and diseases is genome wide association studies (GWAS). Normally the studies are conducted in different populations to replicate the risk loci of specific disease and the number of groups are keep on progressing, including those from Asian country. Computer scientists should be involved in GWAS due to certain problems and the complexity of the processes involved. The problems and past studies related to GWAS are presented in this paper.