Benjamin Redelings

Benjamin Redelings
Research Scholar
Mathematical & Computational Biology
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I am a mathematical and computational biologist.  I use mathematics and computational techniques to answer questions in evolutionary genetics. The mathematics is mostly Bayesian inference and stochastic process modeling. The computation is primarily Markov chain Monte Carlo (MCMC). The evolutionary genetics is focused on inferring evolutionary trees and multiple sequence alignments, but also includes some coalescent theory.

After completing my PhD in Biomathematics at UCLA, I did postdoctoral work at North Carolina, the National Evolutionary Synthesis Center (NESCent), and Duke University.  As of 2017, I’m currently working part-time as a remote postdoc at the University of Kansas on the Open Tree of Life project, and part time on malaria genomics at Duke.

I also develop model-based methods for inferring multiple sequence alignments (MSA) that place insertions and deletions on specific branches of the evolutionary tree, instead of just placing gaps in a matrix. These methods also co-estimate the evolutionary tree along with the alignment. I develop the MCMC software BAli-Phy to perform this estimation.

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Recent publications:

(2017) Redelings BD, Holder MT. A supertree pipeline for summarizing phylogenetic and taxonomic information for millions of species. PeerJ [WWW]

(2015) Redelings BD, Kumagai SK, Wang L, Tatarenkov A, Sakai AK, Weller SG, Culley TM, Avise JC, Uyenoyama MK. A Bayesian Approach to Inferring Rates of Selfing and Locus-Specific Mutation. Genetics 201:1171-1188 [WWW]

(2014) Redelings BD. Erasing Errors Due to Alignment Ambiguity When Estimating Positive Selection. Mol. Biol. Evol. 31(8):1979-1993 [WWW]

Bayesian Statistics, MCMC