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Sergei L. Kosakovsky Pond
Researcher at University of California, San Diego
Publications - 142
Citations - 22134
Sergei L. Kosakovsky Pond is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Population & Phylogenetic tree. The author has an hindex of 61, co-authored 133 publications receiving 19336 citations. Previous affiliations of Sergei L. Kosakovsky Pond include University of California & University of Arizona.
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HyPhy: hypothesis testing using phylogenies
TL;DR: The HyPhypackage is designed to provide a flexible and unified platform for carrying out likelihood-based analyses on multiple alignments of molecular sequence data, with the emphasis on studies of rates and patterns of sequence evolution.
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Not So Different After All: A Comparison of Methods for Detecting Amino Acid Sites Under Selection
TL;DR: Three approaches for estimating the rates of nonsynonymous and synonymous changes at each site in a sequence alignment in order to identify sites under positive or negative selection are considered, suggesting that previously reported differences between results obtained by counting methods and random effects models arise due to a combination of the conservative nature of counting-based methods, the failure of current random effect models to allow for variation in synonymous substitution rates, and the naive application ofrandom effects models to extremely sparse data sets.
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Detecting individual sites subject to episodic diversifying selection.
Ben Murrell,Ben Murrell,Joel O. Wertheim,Sasha Moola,Thomas Weighill,Konrad Scheffler,Konrad Scheffler,Sergei L. Kosakovsky Pond +7 more
TL;DR: It is found that episodic selection is widespread and it is concluded that the number of sites experiencing positive selection may have been vastly underestimated.
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Datamonkey: rapid detection of selective pressure on individual sites of codon alignments
TL;DR: UNLABELLED Datamonkey is a web interface to a suite of cutting edge maximum likelihood-based tools for identification of sites subject to positive or negative selection that are implemented to run in parallel on a cluster of computers.
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Datamonkey 2010
TL;DR: Since the original release in 2005, the analysis options have expanded to include recently developed algorithmic methods for recombination detection, evolutionary fingerprinting of genes, codon model selection, co-evolution between sites, identification of sites, and HIV-1 subtype assignment.