Document Type
Article
Date of Original Version
2008
Department
Computer Science and Statistics
Abstract
The tree representation as a model for organismal evolution has been in use since before Darwin. However, with the recent unprecedented access to biomolecular data, it has been discovered that, especially in the microbial world, individual genes making up the genome of an organism give rise to different and sometimes conflicting evolutionary tree topologies. This discovery calls into question the notion of a single evolutionary tree for an organism and gives rise to the notion of an evolutionary consensus tree based on the evolutionary patterns of the majority of genes in a genome embedded in a network of gene histories. Here, we discuss an approach to the analysis of genomic data of multiple genomes using bipartition spectral analysis and unsupervised learning. An interesting observation is that genes within genomes that have evolutionary tree topologies, which are in substantial conflict with the evolutionary consensus tree of an organism, point to possible horizontal gene transfer events which often delineate significant evolutionary events.
Citation/Publisher Attribution
L. Hamel, N. Nahar, M.S. Poptsova, O. Zhaxybayeva, and J.P. Gogarten, “Unsupervised Learning in Detection of Gene Transfer,” Journal of Biomedicine and Biotechnology, vol. 2008, Article ID 472719, 7 pages, 2008. https://doi.org/10.1155/2008/472719.
Available at: https://doi.org/10.1155/2008/472719
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.