Performance of flip supertree construction with a heuristic algorithm. Export

@article{Eulenstein2004, abstract = {Supertree methods are used to assemble separate phylogenetic trees with shared taxa into larger trees (supertrees) in an effort to construct more comprehensive phylogenetic hypotheses. In spite of much recent interest in supertrees, there are still few methods for supertree construction. The flip supertree problem is an error correction approach that seeks to find a minimum number of changes (flips) to the matrix representation of the set of input trees to resolve their incompatibilities. A previous flip supertree algorithm was limited to finding exact solutions and was only feasible for small input trees. We developed a heuristic algorithm for the flip supertree problem suitable for much larger input trees. We used a series of 48- and 96-taxon simulations to compare supertrees constructed with the flip supertree heuristic algorithm with supertrees constructed using other approaches, including MinCut (MC), modified MC (MMC), and matrix representation with parsimony (MRP). Flip supertrees are generally far more accurate than supertrees constructed using MC or MMC algorithms and are at least as accurate as supertrees built with MRP. The flip supertree method is therefore a viable alternative to other supertree methods when the number of taxa is large.}, author = {Eulenstein, Oliver and Chen, Duhong and Burleigh, Gordon J. and Baca, David F. and Sanderson, Michael J.}, citeulike-article-id = {757481}, citeulike-linkout-0 = {http://dx.doi.org/10.1080/10635150490423719}, doi = {10.1080/10635150490423719}, journal = {Syst Biol}, keywords = {15205054, algorithms, alligators, and, animals, bibtex-import, classification, comparative, computer, crocodiles, data, design, govt, interpretation, meta-analysis, non-phs, phylogeny, research, simulation, statistical, study, support, us}, month = {Apr}, number = {2}, pages = {299--308}, posted-at = {2006-07-13 16:23:34}, priority = {2}, title = {Performance of flip supertree construction with a heuristic algorithm.}, url = {10.1080/10635150490423719}, volume = {53}, year = {2004} }

TY - JOUR ID - Eulenstein2004 L3 - citeulike-article-id:757481 N2 - Supertree methods are used to assemble separate phylogenetic trees with shared taxa into larger trees (supertrees) in an effort to construct more comprehensive phylogenetic hypotheses. In spite of much recent interest in supertrees, there are still few methods for supertree construction. The flip supertree problem is an error correction approach that seeks to find a minimum number of changes (flips) to the matrix representation of the set of input trees to resolve their incompatibilities. A previous flip supertree algorithm was limited to finding exact solutions and was only feasible for small input trees. We developed a heuristic algorithm for the flip supertree problem suitable for much larger input trees. We used a series of 48- and 96-taxon simulations to compare supertrees constructed with the flip supertree heuristic algorithm with supertrees constructed using other approaches, including MinCut (MC), modified MC (MMC), and matrix representation with parsimony (MRP). Flip supertrees are generally far more accurate than supertrees constructed using MC or MMC algorithms and are at least as accurate as supertrees built with MRP. The flip supertree method is therefore a viable alternative to other supertree methods when the number of taxa is large. IS - 2 JF - Syst Biol EP - 308 TI - Performance of flip supertree construction with a heuristic algorithm. VL - 53 SP - 299 KW - 15205054 KW - algorithms KW - alligators KW - and KW - animals KW - bibtex-import KW - classification KW - comparative KW - computer KW - crocodiles KW - data KW - design KW - govt KW - interpretation KW - meta-analysis KW - non-phs KW - phylogeny KW - research KW - simulation KW - statistical KW - study KW - support KW - us AU - Eulenstein, Oliver AU - Chen, Duhong AU - Burleigh, Gordon AU - Baca, David AU - Sanderson, Michael PY - 2004/Apr// UR - http://dx.doi.org/10.1080/10635150490423719 ER -