Seeing the trees and their branches in the network is hard
Theoretical Computer Science
Novel Phylogenetic Network Inference by Combining Maximum Likelihood and Hidden Markov Models
WABI '08 Proceedings of the 8th international workshop on Algorithms in Bioinformatics
Integrating Sequence and Topology for Efficient and Accurate Detection of Horizontal Gene Transfer
RECOMB-CG '08 Proceedings of the international workshop on Comparative Genomics
Parsimony Score of Phylogenetic Networks: Hardness Results and a Linear-Time Heuristic
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Comparison of Tree-Child Phylogenetic Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
RECOMB-CG '09 Proceedings of the International Workshop on Comparative Genomics
Faster computation of the Robinson-Foulds distance between phylogenetic networks
CPM'10 Proceedings of the 21st annual conference on Combinatorial pattern matching
Simultaneous Identification of Duplications and Lateral Gene Transfers
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Faster computation of the Robinson-Foulds distance between phylogenetic networks
Information Sciences: an International Journal
RECOMB'12 Proceedings of the 16th Annual international conference on Research in Computational Molecular Biology
Simultaneous Identification of Duplications, Losses, and Lateral Gene Transfers
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
WABI'07 Proceedings of the 7th international conference on Algorithms in Bioinformatics
| Hi-index | 3.84 |
Motivation: Horizontal gene transfer (HGT) is believed to be ubiquitous among bacteria, and plays a major role in their genome diversification as well as their ability to develop resistance to antibiotics. In light of its evolutionary significance and implications for human health, developing accurate and efficient methods for detecting and reconstructing HGT is imperative. Results: In this article we provide a new HGT-oriented likelihood framework for many problems that involve phylogeny-based HGT detection and reconstruction. Beside the formulation of various likelihood criteria, we show that most of these problems are NP-hard, and offer heuristics for efficient and accurate reconstruction of HGT under these criteria. We implemented our heuristics and used them to analyze biological as well as synthetic data. In both cases, our criteria and heuristics exhibited very good performance with respect to identifying the correct number of HGT events as well as inferring their correct location on the species tree. Availability: Implementation of the criteria as well as heuristics and hardness proofs are available from the authors upon request. Hardness proofs can also be downloaded at http://www.cs.tau.ac.il/~tamirtul/MLNET/Supp-ML.pdf Contact: tamirtul@post.tau.ac.il Supplementary information: Supplementary data are available at Bioinformatics online.