Who is Who in Phylogenetic Networks

Publications of Wing-Kai Hon     Order by:   Type | Year

Associated keywords

compression counting explicit-network from-distances from-rooted-trees galled-tree k-reticulated phylogenetic-network phylogeny polynomial Program-ARTNET Program-CMPT reconstruction

2018

1 Kuang-Yu Chang, Yun Cui, Siu-Ming Yiu and Wing-Kai Hon. Reconstructing One-Articulated Networks with Distance Matrices. In JCB, Vol. 25(3):253-269, 2018. Keywords: explicit network, from distances, k-reticulated, phylogenetic network, phylogeny, reconstruction.         2 Kuang-Yu Chang, Wing-Kai Hon and Sharma V. Thankachan. Compact Encoding for Galled-Trees and its Applications. In 2018 Data Compression Conference, Pages 297-306, 2018. Keywords: compression, counting, explicit network, galled tree, phylogenetic network, polynomial.

2017

3 Kuang-Yu Chang, Yun Cui, Siu-Ming Yiu and Wing-Kai Hon. Reconstructing One-Articulated Networks with Distance Matrices. In ISBRA17, Vol. 10330:34-45 of LNCS, Springer, 2017. Keywords: explicit network, from distances, k-reticulated, phylogenetic network, phylogeny, reconstruction. Note: https://link.springer.com/content/pdf/10.1007%2F978-3-319-59575-7.pdf#page=100.

2013

4 Hoa Vu, Francis Chin, Wing-Kai Hon, Henry Leung, Kunihiko Sadakane, Wing-Kin Sung and Siu-Ming Yiu. Reconstructing k-Reticulated Phylogenetic Network from a Set of Gene Trees. In ISBRA13, Vol. 7875:112-124 of LNCS, springer, 2013. Keywords: from rooted trees, k-reticulated, phylogenetic network, phylogeny, polynomial, Program ARTNET, Program CMPT, reconstruction. Note: http://grid.cs.gsu.edu/~xguo9/publications/2013_Cloud%20computing%20for%20de%20novo%20metagenomic%20sequence%20assembly.pdf#page=123.         Toggle abstract "The time complexity of existing algorithms for reconstructing a level-x phylogenetic network increases exponentially in x. In this paper, we propose a new classification of phylogenetic networks called k-reticulated network. A k-reticulated network can model all level-k networks and some level-x networks with x > k. We design algorithms for reconstructing k-reticulated network (k = 1 or 2) with minimum number of hybrid nodes from a set of m binary trees, each with n leaves in O(mn 2) time. The implication is that some level-x networks with x > k can now be reconstructed in a faster way. We implemented our algorithm (ARTNET) and compared it with CMPT. We show that ARTNET outperforms CMPT in terms of running time and accuracy. We also consider the case when there does not exist a 2-reticulated network for the input trees. We present an algorithm computing a maximum subset of the species set so that a new set of subtrees can be combined into a 2-reticulated network. © 2013 Springer-Verlag."