DLS-trees: a model of evolutionary scenarios
Theoretical Computer Science
Algorithms for Exploring the Space of Gene Tree/Species Tree Reconciliations
RECOMB-CG '08 Proceedings of the international workshop on Comparative Genomics
The gene evolution model and computing its associated probabilities
Journal of the ACM (JACM)
Generalized Binary Tanglegrams: Algorithms and Applications
BICoB '09 Proceedings of the 1st International Conference on Bioinformatics and Computational Biology
The Gene-Duplication Problem: Near-Linear Time Algorithms for NNI-Based Local Searches
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
New Perspectives on Gene Family Evolution: Losses in Reconciliation and a Link with Supertrees
RECOMB 2'09 Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology
Inferring a duplication, speciation and loss history from a gene tree
RECOMB-CG'07 Proceedings of the 2007 international conference on Comparative genomics
Improving inference of transcriptional regulatory networks based on network evolutionary models
WABI'09 Proceedings of the 9th international conference on Algorithms in bioinformatics
H-trees: a Model of Evolutionary Scenarios with Horizontal Gene Transfer
Fundamenta Informaticae - From Mathematical Beauty to the Truth of Nature: to Jerzy Tiuryn on his 60th Birthday
Simultaneous Identification of Duplications and Lateral Gene Transfers
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Algorithms for rapid error correction for the gene duplication problem
ISBRA'11 Proceedings of the 7th international conference on Bioinformatics research and applications
ProPhyC: a probabilistic phylogenetic model for refining regulatory networks
ISBRA'11 Proceedings of the 7th international conference on Bioinformatics research and applications
An improved algorithm for the macro-evolutionary phylogeny problem
CPM'06 Proceedings of the 17th Annual conference on Combinatorial Pattern Matching
A hybrid micro-macroevolutionary approach to gene tree reconstruction
RECOMB'05 Proceedings of the 9th Annual international conference on Research in Computational Molecular Biology
On the structure of reconciliations
RCG'04 Proceedings of the 2004 RECOMB international conference on Comparative Genomics
Refining Regulatory Networks through Phylogenetic Transfer of Information
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Inferring evolutionary scenarios in the duplication, loss and horizontal gene transfer model
Logic and Program Semantics
Generalized k-ary tanglegrams on level graphs: A satisfiability-based approach and its evaluation
Discrete Applied Mathematics
Minimum leaf removal for reconciliation: complexity and algorithms
CPM'12 Proceedings of the 23rd Annual conference on Combinatorial Pattern Matching
An optimal reconciliation algorithm for gene trees with polytomies
WABI'12 Proceedings of the 12th international conference on Algorithms in Bioinformatics
Gene tree correction for reconciliation and species tree inference: Complexity and algorithms
Journal of Discrete Algorithms
Hi-index | 0.01 |
Gene tree and species tree reconstruction, orthology analysis and reconciliation, are problems important in multigenome-based comparative genomics and biology in general. In the present paper, we advance the frontier of these areas in several respects and provide important computational tools. First, exact algorithms are given for several probabilistic reconciliation problems with respect to the probabilistic gene evolution model, previously developed by the authors. Until now, those problems were solved by MCMC estimation algorithms. Second, we extend the gene evolution model to the gene sequence evolution model, by including sequence evolution. Third, we develop MCMC algorithms for the gene sequence evolution model that, given gene sequence data allows: (1) orthology analysis, reconciliation analysis, and gene tree reconstruction, w.r.t. a species tree, that balances a likely/unlikely reconciliation and a likely/unlikely gene tree and (2) species tree reconstruction that balance a likely/unlikely reconciliation and a likely/unlikely gene trees. These MCMC algorithms take advantage of the exact algorithms for the gene evolution model. We have successfully tested our dynamical programming algorithms on real data for a biogeography problem. The MCMC algorithms perform very well both on synthetic and biological data.