Literature DB >> 23877343

Biological intuition in alignment-free methods: response to Posada.

Mark A Ragan1, Cheong Xin Chan.   

Abstract

A recent editorial in Journal of Molecular Evolution highlights opportunities and challenges facing molecular evolution in the era of next-generation sequencing. Abundant sequence data should allow more-complex models to be fit at higher confidence, making phylogenetic inference more reliable and improving our understanding of evolution at the molecular level. However, concern that approaches based on multiple sequence alignment may be computationally infeasible for large datasets is driving the development of so-called alignment-free methods for sequence comparison and phylogenetic inference. The recent editorial characterized these approaches as model-free, not based on the concept of homology, and lacking in biological intuition. We argue here that alignment-free methods have not abandoned models or homology, and can be biologically intuitive.

Mesh:

Year:  2013        PMID: 23877343     DOI: 10.1007/s00239-013-9573-0

Source DB:  PubMed          Journal:  J Mol Evol        ISSN: 0022-2844            Impact factor:   2.395


  9 in total

1.  The pace and proliferation of biological technologies.

Authors:  Robert Carlson
Journal:  Biosecur Bioterror       Date:  2003

2.  Alignment-free sequence comparison (II): theoretical power of comparison statistics.

Authors:  Lin Wan; Gesine Reinert; Fengzhu Sun; Michael S Waterman
Journal:  J Comput Biol       Date:  2010-10-25       Impact factor: 1.479

3.  Phylogenetic models of molecular evolution: next-generation data, fit, and performance.

Authors:  David Posada
Journal:  J Mol Evol       Date:  2013-05-22       Impact factor: 2.395

4.  Alignment-free sequence comparison (I): statistics and power.

Authors:  Gesine Reinert; David Chew; Fengzhu Sun; Michael S Waterman
Journal:  J Comput Biol       Date:  2009-12       Impact factor: 1.479

5.  Alignment-free detection of local similarity among viral and bacterial genomes.

Authors:  Mirjana Domazet-Lošo; Bernhard Haubold
Journal:  Bioinformatics       Date:  2011-04-06       Impact factor: 6.937

6.  The real cost of sequencing: higher than you think!

Authors:  Andrea Sboner; Xinmeng Jasmine Mu; Dov Greenbaum; Raymond K Auerbach; Mark B Gerstein
Journal:  Genome Biol       Date:  2011-08-25       Impact factor: 13.583

Review 7.  Bringing molecules back into molecular evolution.

Authors:  Claus O Wilke
Journal:  PLoS Comput Biol       Date:  2012-06-28       Impact factor: 4.475

8.  Bayesian and maximum likelihood phylogenetic analyses of protein sequence data under relative branch-length differences and model violation.

Authors:  Jessica C Mar; Timothy J Harlow; Mark A Ragan
Journal:  BMC Evol Biol       Date:  2005-01-28       Impact factor: 3.260

9.  Next-generation phylogenomics.

Authors:  Cheong Xin Chan; Mark A Ragan
Journal:  Biol Direct       Date:  2013-01-22       Impact factor: 4.540

  9 in total
  4 in total

1.  Inferring phylogenies of evolving sequences without multiple sequence alignment.

Authors:  Cheong Xin Chan; Guillaume Bernard; Olivier Poirion; James M Hogan; Mark A Ragan
Journal:  Sci Rep       Date:  2014-09-30       Impact factor: 4.379

2.  k-mer Similarity, Networks of Microbial Genomes, and Taxonomic Rank.

Authors:  Guillaume Bernard; Paul Greenfield; Mark A Ragan; Cheong Xin Chan
Journal:  mSystems       Date:  2018-11-20       Impact factor: 6.496

3.  Alignment-Free Analysis of Whole-Genome Sequences From Symbiodiniaceae Reveals Different Phylogenetic Signals in Distinct Regions.

Authors:  Rosalyn Lo; Katherine E Dougan; Yibi Chen; Sarah Shah; Debashish Bhattacharya; Cheong Xin Chan
Journal:  Front Plant Sci       Date:  2022-04-26       Impact factor: 6.627

Review 4.  Molecular phylogenetics before sequences: oligonucleotide catalogs as k-mer spectra.

Authors:  Mark A Ragan; Guillaume Bernard; Cheong Xin Chan
Journal:  RNA Biol       Date:  2014-01-14       Impact factor: 4.652

  4 in total

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