Computational experiments on algorithms for haplotype inference problems by pure parsimony

I. Lin Wang, Hui E. Yang

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

To analyze the function of DNA, researchers have to obtain each haplotype, the genetic constitution of an individual chromosome, of an individual for analysis. Due to the significant efforts required in collecting haplotypes, the descriptions of one conflated pair of haplotypes called genotypes are usually collected. Since the genotype data contains insufficient information to identify the combination of DNA sequence in each copy of a chromosome, one has to solve the population haplotype inference problem by pure parsimony criterion which uses the minimum number of haplotypes to infer the haplotype data from genotype data for a population. Previous researches use mathematical programming methods such as integer programming and semidefinite programming models to solve the population haplotype inference problem. However, no computational experiment has ever been conducted to evaluate the algorithmic effectiveness. This paper thus conducts the first computational experiments on four haplotyping algorithms, including our new greedy heuristic and three pervious haplotyping algorithms.

原文English
主出版物標題Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006
DOIs
出版狀態Published - 2006
事件9th Joint Conference on Information Sciences, JCIS 2006 - Taiwan, ROC, Taiwan
持續時間: 2006 十月 82006 十月 11

出版系列

名字Proceedings of the 9th Joint Conference on Information Sciences, JCIS 2006
2006

Other

Other9th Joint Conference on Information Sciences, JCIS 2006
國家/地區Taiwan
城市Taiwan, ROC
期間06-10-0806-10-11

All Science Journal Classification (ASJC) codes

  • 工程 (全部)

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