TY - GEN
T1 - A new linear-time heuristic algorithm for computing the parsimony score of phylogenetic networks
T2 - 3rd International Symposium Bioinformatics Research and Applications, ISBRA 2007
AU - Jin, Guohua
AU - Nakhleh, Luay
AU - Snir, Sagi
AU - Tuller, Tamir
PY - 2007
Y1 - 2007
N2 - Phylogenies play a major role in representing the interrelationships among biological entities. Many methods for reconstructing and studying such phylogenies have been proposed, almost all of which assume that the underlying history of a given set of species can be represented by a binary tree. Although many biological processes can be effectively modeled and summarized in this fashion, others cannot: recombination, hybrid speciation, and horizontal gene transfer result in networks, rather than trees, of relationships. In a series of papers, we have extended the maximum parsimony (MP) criterion to phylogenetic networks, demonstrated its appropriateness, and established the intractability of the problem of scoring the parsimony of a phylogenetic network. In this work we show the hardness of approximation for the general case of the problem, devise a very fast (linear-time) heuristic algorithm for it, and implement it on simulated as well as biological data.
AB - Phylogenies play a major role in representing the interrelationships among biological entities. Many methods for reconstructing and studying such phylogenies have been proposed, almost all of which assume that the underlying history of a given set of species can be represented by a binary tree. Although many biological processes can be effectively modeled and summarized in this fashion, others cannot: recombination, hybrid speciation, and horizontal gene transfer result in networks, rather than trees, of relationships. In a series of papers, we have extended the maximum parsimony (MP) criterion to phylogenetic networks, demonstrated its appropriateness, and established the intractability of the problem of scoring the parsimony of a phylogenetic network. In this work we show the hardness of approximation for the general case of the problem, devise a very fast (linear-time) heuristic algorithm for it, and implement it on simulated as well as biological data.
UR - http://www.scopus.com/inward/record.url?scp=34547474120&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-72031-7_6
DO - 10.1007/978-3-540-72031-7_6
M3 - Conference contribution
AN - SCOPUS:34547474120
SN - 3540720308
SN - 9783540720300
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 61
EP - 72
BT - Bioinformatics Research and Applications - Third International Symposium, ISBRA 2007, Proceedings
PB - Springer Verlag
Y2 - 7 May 2007 through 10 May 2007
ER -