Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4950563 | Future Generation Computer Systems | 2017 | 45 Pages |
Abstract
Our studies reveal that Parallel SuperFine allows to reduce, significantly, the time required to perform supertree estimation. Moreover, we show that Parallel SuperFine exhibits good scalability, even in the presence of asymmetric biological data sets. Furthermore, the achieved results enable to conclude that the radical improvement in performance does not impair tree accuracy, which is a key issue in phylogenetic inference.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Diogo Telmo Neves, João LuÃs Sobral,