eCite Digital Repository

On mechanistic modeling of gene content evolution: birth-death models and mechanisms of gene birth and gene retention

Citation

Teufel, AI and Zhao, J and O'Reilly, M and Liu, L and Liberles, DA, On mechanistic modeling of gene content evolution: birth-death models and mechanisms of gene birth and gene retention, Computation, 2, (3) pp. 112-130. ISSN 2079-3197 (2014) [Refereed Article]


Preview
PDF
942Kb
  

Copyright Statement

Licensed under Creative Commons Attribution 3.0 Unported (CC BY 3.0) http://creativecommons.org/licenses/by/3.0/

Official URL: http://www.mdpi.com/2079-3197/2/3/112

DOI: doi:10.3390/computation2030112

Abstract

Characterizing the mechanisms of duplicate gene retention using phylogenetic methods requires models that are consistent with different biological processes. The interplay between complex biological processes and necessarily simpler statistical models leads to a complex modeling problem. A discussion of the relationship between biological processes, existing models for duplicate gene retention and data is presented. Existing models are then extended in deriving two new birth/death models for phylogenetic application in a gene tree/species tree reconciliation framework to enable probabilistic inference of the mechanisms from model parameterization. The goal of this work is to synthesize a detailed discussion of modeling duplicate genes to address biological questions, moving from previous work to future trajectories with the aim of generating better models and better inference.

Item Details

Item Type:Refereed Article
Keywords:gene duplication, gene loss, phylogeny, gene tree/species tree reconciliation, stochastic models, birth/death processes
Research Division:Mathematical Sciences
Research Group:Statistics
Research Field:Stochastic Analysis and Modelling
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Mathematical Sciences
Author:O'Reilly, M (Dr Malgorzata O'Reilly)
ID Code:94797
Year Published:2014
Deposited By:Mathematics and Physics
Deposited On:2014-09-17
Last Modified:2015-04-24
Downloads:243 View Download Statistics

Repository Staff Only: item control page