Cited By
View all- Shang JWang XWu XSun YDing QLiu JZhang H(2019)A Review of Ant Colony Optimization Based Methods for Detecting Epistatic InteractionsIEEE Access10.1109/ACCESS.2019.28946767(13497-13509)Online publication date: 2019
A New Epistasis Detecting Algorithm Based on Ant Colony Optimization
Authors: 
Zhihui Zhou, Guixia Liu, Lingtao Su, Liang Han, Lun YanAuthors Info & Claims
Pages 226 - 231
Abstract
The rapid developments of chip-based technology have greatly improved human genetics and made routine the access of thousands of single nucleotide polymorphisms (SNPs) contributing to an informatics challenge. The characterization and interpretation of genes and gene-gene interactions that affect the susceptibility of common, complex multifactorial diseases is a computational and statistical challenge in genome-wide association studies (GWAS). Various methods have been proposed, but they have difficulty to be directly applied to GWAS caused by excessive search space and intensive computational burden. In this paper, we propose an ant colony optimization (ACO) based algorithm by combining the pheromone updating rule with the heuristic information. We tested power performance of our algorithm by conducting sufficient experiments including a wide range of simulated datasets experiments and a real genome-wide dataset experiment. Experimental results demonstrate that our algorithm is time efficient and gain good performance in the term of the power of prediction accuracy.
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- A New Epistasis Detecting Algorithm Based on Ant Colony Optimization
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Published In
July 2014
430 pages
ISBN:9781450328104
DOI:10.1145/2632856
- General Chairs:
- Hanzi Wang,
- Larry Davis,
- Program Chairs:
- Wenwu Zhu,
- Stephan Kopf,
- Yanyun Qu,
- Publications Chairs:
- Jun Yu,
- Jitao Sang,
- Tao Mei
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In-Cooperation
- NSF of China: National Natural Science Foundation of China
- Beijing ACM SIGMM Chapter
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Association for Computing Machinery
New York, NY, United States
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Published: 10 July 2014
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ICIMCS '14
ICIMCS '14: International Conference on Internet Multimedia Computing and Service
July 10 - 12, 2014
Xiamen, China
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View all- Shang JWang XWu XSun YDing QLiu JZhang H(2019)A Review of Ant Colony Optimization Based Methods for Detecting Epistatic InteractionsIEEE Access10.1109/ACCESS.2019.28946767(13497-13509)Online publication date: 2019
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