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Christopher Oldmeadow

dblp:75/9181 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2011
0000-0001-6104-1322ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
molecular evolution
0.112011
Model selection in Bayesian segmentation of multiple DNA alignments · Bioinform. 2011
Bioinformatics and computational biology › multiple sequence alignment
multiple sequence alignment analysis
0.112011
Model selection in Bayesian segmentation of multiple DNA alignments · Bioinform. 2011

Methods — techniques the papers use, named apart from their topics

markov chain monte carlo · 0.1deviance information criterion · 0.1bayesian segmentation · 0.1
YearPublicationVenuePosition
2011 Model selection in Bayesian segmentation of multiple DNA alignments
abstract
MOTIVATION: The analysis of multiple sequence alignments is allowing researchers to glean valuable insights into evolution, as well as identify genomic regions that may be functional, or discover novel classes of functional elements. Understanding the distribution of conservation levels that constitutes the evolutionary landscape is crucial to distinguishing functional regions from non-functional. Recent evidence suggests that a binary classification of evolutionary rates is inappropriate for this purpose and finds only highly conserved functional elements. Given that the distribution of evolutionary rates is multi-modal, determining the number of modes is of paramount concern. Through simulation, we evaluate the performance of a number of information criterion approaches derived from MCMC simulations in determining the dimension of a model. RESULTS: We utilize a deviance information criterion (DIC) approximation that is more robust than the approximations from other information criteria, and show our information criteria approximations do not produce superfluous modes when estimating conservation distributions under a variety of circumstances. We analyse the distribution of conservation for a multiple alignment comprising four primate species and mouse, and repeat this on two additional multiple alignments of similar species. We find evidence of six distinct classes of evolutionary rates that appear to be robust to the species used. AVAILABILITY: Source code and data are available at http://dl.dropbox.com/u/477240/changept.zip.
Christopher Oldmeadow, Jonathan M. Keith
Bioinform.1