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John P. Huelsenbeck

dblp:22/4634 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2004
0000-0002-3050-9997ORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 3 · 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
3 papers
Bioinformatics and computational biology · 100%
Computer architecture, parallel and distributed computing, and storage systems
2 papers
Parallel and multicore computing · 100%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › phylogenetics › phylogenetic inference
bayesian phylogenetic inference
0.132004
Parallel Metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference · Bioinform. 2004
MrBayes 3: Bayesian phylogenetic inference under mixed models · Bioinform. 2003
MRBAYES: Bayesian inference of phylogenetic trees · Bioinform. 2001
Bioinformatics and computational biology › phylogenetics
phylogenetic inference
0.132004
Parallel Metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference · Bioinform. 2004
MrBayes 3: Bayesian phylogenetic inference under mixed models · Bioinform. 2003
MRBAYES: Bayesian inference of phylogenetic trees · Bioinform. 2001
Bioinformatics and computational biology
markov chain monte carlo
0.012004
Parallel Metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference · Bioinform. 2004
Parallel and multicore computing
parallel programming models
0.012004
Parallel Metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference · Bioinform. 2004
Parallel and multicore computing › parallel programming models › hybrid programming models
shared memory and message passing
0.012004
Parallel Metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference · Bioinform. 2004
Parallel and multicore computing › MPI
MPI-based parallelization
0.012003
MrBayes 3: Bayesian phylogenetic inference under mixed models · Bioinform. 2003
Parallel and multicore computing
parallel computing
0.012003
MrBayes 3: Bayesian phylogenetic inference under mixed models · Bioinform. 2003

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

markov chain monte carlo · 0.1parallel programming · 0.1Metropolis coupled MCMC · 0.1metropolis coupling · 0.1MPI · 0.1
YearPublicationVenuePosition
2004 Parallel Metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference
abstract
MOTIVATION: Bayesian estimation of phylogeny is based on the posterior probability distribution of trees. Currently, the only numerical method that can effectively approximate posterior probabilities of trees is Markov chain Monte Carlo (MCMC). Standard implementations of MCMC can be prone to entrapment in local optima. Metropolis coupled MCMC [(MC)(3)], a variant of MCMC, allows multiple peaks in the landscape of trees to be more readily explored, but at the cost of increased execution time. RESULTS: This paper presents a parallel algorithm for (MC)(3). The proposed parallel algorithm retains the ability to explore multiple peaks in the posterior distribution of trees while maintaining a fast execution time. The algorithm has been implemented using two popular parallel programming models: message passing and shared memory. Performance results indicate nearly linear speed improvement in both programming models for small and large data sets.
Gautam Altekar, Sandhya Dwarkadas, John P. Huelsenbeck, Fredrik Ronquist
Bioinform.3
2003 MrBayes 3: Bayesian phylogenetic inference under mixed models
abstract
Abstract Summary: MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models. This allows the user to analyze heterogeneous data sets consisting of different data types—e.g. morphological, nucleotide, and protein—and to explore a wide variety of structured models mixing partition-unique and shared parameters. The program employs MPI to parallelize Metropolis coupling on Macintosh or UNIX clusters. Availability: http://morphbank.ebc.uu.se/mrbayes Contact: [email protected] * To whom correspondence should be addressed.
Fredrik Ronquist, John P. Huelsenbeck
Bioinform.2
2001 MRBAYES: Bayesian inference of phylogenetic trees
abstract
SUMMARY: The program MRBAYES performs Bayesian inference of phylogeny using a variant of Markov chain Monte Carlo. AVAILABILITY: MRBAYES, including the source code, documentation, sample data files, and an executable, is available at http://brahms.biology.rochester.edu/software.html.
John P. Huelsenbeck, Fredrik Ronquist
Bioinform.1