Phylogenetic Trees in Bioinformatics

Title: Phylogenetic Trees in Bioinformatics

Volume: 5 Issue: 1

Author(s): Tom Burr

Affiliation:

Keywords: Phylogenetic trees, nucleotide substitution models, inference methods, bootstrap, Markov Chain Monte Carlo, population history

Abstract: Genetic data is often used to infer evolutionary relationships among a collection of viruses, bacteria, animal or plant species, or other operational taxonomic units (OTU). A phylogenetic tree depicts such relationships and provides a visual representation of the estimated branching order of the OTUs. Tree estimation is unique for several reasons, including the types of data used to represent each OTU; the use of probabilistic nucleotide substitution models; the inference goals involving both tree topology and branch length, and the huge number of possible trees for a given sample of a very modest number of OTUs, which implies that finding the best tree(s) to describe the genetic data for each OTU is computationally demanding. Bioinformatics is too large a field to review here. We focus on that aspect of bioinformatics that includes study of similarities in genetic data from multiple OTUs. Although research questions are diverse, a common underlying challenge is to estimate the evolutionary history of the OTUs. Therefore, this paper reviews the role of phylogenetic tree estimation in bioinformatics, available methods and software, and identifies areas for additional research and development.

Cite this article as:

Burr Tom, Phylogenetic Trees in Bioinformatics, Current Bioinformatics 2010; 5 (1) . https://dx.doi.org/10.2174/157489310790596367