A Classification Based Approach for Root Unknown Phylogenetic Networks Under Constrained Recombination

Phylogenetic networks are the generalization of the tree models used to represent evolutionary relationship between the species. Tree models of evolutionary process are not adequate to represent the evolutionary events such as, hybridization, lateral/ horizontal gene transfer and genetic recombination. A well-formulated problem in phylogenetic networks, due to recombination, is to derive a set of input sequences on a network with minimum number of recombinations. No efficient algorithm exists for this problem as it is known to be NP-hard. Efficient solutions exist for the constrained recombination networks, where the nodes on each recombination cycles are disjoint. These solutions are based on the assumption that the ancestral sequence is known in advance. On the other hand, the more biologically realistic case is that where the ancestor sequence is not known in advance. In this paper we propose an efficient classification based method for deriving a phylogenetic network under constrained recombination without knowing the ancestral sequence.