A Machine Learning Method for Detecting Autocorrelation of Evolutionary Rates in Large Phylogenies

Volume: 36, Issue: 4, Pages: 811 - 824
Published: Jan 23, 2019
Abstract
New species arise from pre-existing species and inherit similar genomes and environments. This predicts greater similarity of the tempo of molecular evolution between direct ancestors and descendants, resulting in autocorrelation of evolutionary rates in the tree of life. Surprisingly, molecular sequence data have not confirmed this expectation, possibly because available methods lack the power to detect autocorrelated rates. Here, we present a...
Paper Details
Title
A Machine Learning Method for Detecting Autocorrelation of Evolutionary Rates in Large Phylogenies
Published Date
Jan 23, 2019
Volume
36
Issue
4
Pages
811 - 824
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.