Literature DB >> 16226061

Phylogenetics by likelihood: evolutionary modeling as a tool for understanding the genome.

Carolin Kosiol1, Lee Bofkin, Simon Whelan.   

Abstract

Molecular evolutionary studies provide a means of investigating how cells function and how organisms adapt to their environment. The products of evolutionary studies provide medically important insights to the source of major diseases, such as HIV, and hold the key to understand the developing immunity of pathogenic bacteria to antibiotics. They have also helped mankind understand its place in nature, casting light on the selective forces and environmental conditions that resulted in modern humans. The use of likelihood as a framework for statistical modeling in phylogenetics has played a fundamental role in studying molecular evolution, enabling rigorous and robust conclusions to be drawn from sequence data. The first half of this article is a general introduction to the likelihood method for inferring phylogenies, the properties of the models used, and how it can be used for statistical testing. The latter half of the article focuses on the emerging new generation of phylogenetic models that describe heterogeneity in the evolutionary process along sequences, including the recoding of protein coding sequence data to amino acids and codons, and various approaches for describing dependencies between sites in a sequence. We conclude with a detailed case study examining how modern modeling approaches have been successfully employed to identify adaptive evolution in proteins.

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Year:  2005        PMID: 16226061     DOI: 10.1016/j.jbi.2005.08.003

Source DB:  PubMed          Journal:  J Biomed Inform        ISSN: 1532-0464            Impact factor:   6.317


  7 in total

1.  A Phylogenetic Rate Parameter Indicates Different Sequence Divergence Patterns in Orthologs and Paralogs.

Authors:  Joseph B Ahrens; Ashley I Teufel; Jessica Siltberg-Liberles
Journal:  J Mol Evol       Date:  2020-10-29       Impact factor: 2.395

2.  Continent-wide evolutionary trends of emerging SARS-CoV-2 variants: dynamic profiles from Alpha to Omicron.

Authors:  Chiranjib Chakraborty; Manojit Bhattacharya; Ashish Ranjan Sharma; Kuldeep Dhama; Sang-Soo Lee
Journal:  Geroscience       Date:  2022-07-13       Impact factor: 7.581

3.  Evolution of endogenous retroviruses in the Suidae: evidence for different viral subpopulations in African and Eurasian host species.

Authors:  Fabrícia F Nascimento; Jaime Gongora; Michael Charleston; Michael Tristem; Stewart Lowden; Chris Moran
Journal:  BMC Evol Biol       Date:  2011-05-24       Impact factor: 3.260

4.  Evidence of Statistical Inconsistency of Phylogenetic Methods in the Presence of Multiple Sequence Alignment Uncertainty.

Authors:  A S Md Mukarram Hossain; Benjamin P Blackburne; Abhijeet Shah; Simon Whelan
Journal:  Genome Biol Evol       Date:  2015-07-01       Impact factor: 3.416

5.  Adaptive Evolution of the Fox Coronavirus Based on Genome-Wide Sequence Analysis.

Authors:  Chunyu Feng; Yuting Liu; Guangqi Lyu; Songyang Shang; Hongyue Xia; Junpeng Zhang; David M Irwin; Zhe Wang; Shuyi Zhang
Journal:  Biomed Res Int       Date:  2022-04-13       Impact factor: 3.246

Review 6.  Structural conservation of a short, functional, peptide-sequence motif.

Authors:  Susan Fox-Erlich; Martin R Schiller; Michael R Gryk
Journal:  Front Biosci (Landmark Ed)       Date:  2009-01-01

7.  Adaptive Evolution of Feline Coronavirus Genes Based on Selection Analysis.

Authors:  Hongyue Xia; Xibao Li; Wenliang Zhao; Shuran Jia; Xiaoqing Zhang; David M Irwin; Shuyi Zhang
Journal:  Biomed Res Int       Date:  2020-08-13       Impact factor: 3.411

  7 in total

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