Document Detail


The undirected incomplete perfect phylogeny problem.
MedLine Citation:
PMID:  18989047     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The incomplete perfect phylogeny (IPP) problem and the incomplete perfect phylogeny haplotyping (IPPH) problem deal with constructing a phylogeny for a given set of haplotypes or genotypes with missing entries. The earlier approaches for both of these problems dealt with restricted versions of the problems, where the root is either available or can be trivially re-constructed from the data, or certain assumptions were made about the data. In this paper, we deal with the unrestricted versions of the problems, where the root of the phylogeny is neither available nor trivially recoverable from the data. Both IPP and IPPH problems have previously been proven to be NP-complete. Here, we present efficient enumerative algorithms that can handle practical instances of the problem. Empirical analysis on simulated data shows that the algorithms perform very well both in terms of speed and in terms accuracy of the recovered data.
Authors:
Ravi Vijaya Satya; Amar Mukherjee
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM     Volume:  5     ISSN:  1557-9964     ISO Abbreviation:  IEEE/ACM Trans Comput Biol Bioinform     Publication Date:    2008 Oct-Dec
Date Detail:
Created Date:  2008-11-07     Completed Date:  2009-01-30     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101196755     Medline TA:  IEEE/ACM Trans Comput Biol Bioinform     Country:  United States    
Other Details:
Languages:  eng     Pagination:  618-29     Citation Subset:  IM    
Affiliation:
School of Electrical Engineering and Computer Science, University of Central Florida, 4000 Central Florida Blvd., Orlando, FL 32816., USA. ravi.vijayasatya@gmail.com
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Chromosome Mapping / methods*
Evolution*
Evolution, Molecular*
Haplotypes / genetics*
Phylogeny*
Polymorphism, Single Nucleotide / genetics*
Sequence Analysis, DNA / methods*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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