This paper deals with the computational problem of inferring complete information on haplotypes from haplotypes with missing data. This problem is one of the main issues in haplotyping, as the current DNA sequencing technology often produces haplotypes with missing bases and thus the complete information on haplotypes has to be inferred through computational methods. In this paper we propose a new algorithmic approach to the problem that assumes both the Coalescent and the Minimum Entropy models and we provide an experimental analysis relating it to the previously investigated approaches. In particular, the reconstruction of a perfect phylogeny from haplotypes with missing data is addressed
Bonizzoni, P., DELLA VEDOVA, G., Dondi, R., Mariani, L. (2005). Experimental Analysis of a New Algorithm for Partial Haplotype Completion. In 5th International Conference on Computational Science - ICCS 2005; Atlanta, GA; United States; 22 May 2005 through 25 May 2005 (pp.952-959). Springer Verlag [10.1007/11428848_121].
Experimental Analysis of a New Algorithm for Partial Haplotype Completion
BONIZZONI, PAOLA;DELLA VEDOVA, GIANLUCA;
2005
Abstract
This paper deals with the computational problem of inferring complete information on haplotypes from haplotypes with missing data. This problem is one of the main issues in haplotyping, as the current DNA sequencing technology often produces haplotypes with missing bases and thus the complete information on haplotypes has to be inferred through computational methods. In this paper we propose a new algorithmic approach to the problem that assumes both the Coalescent and the Minimum Entropy models and we provide an experimental analysis relating it to the previously investigated approaches. In particular, the reconstruction of a perfect phylogeny from haplotypes with missing data is addressed
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