Bret Larget

33.6k citations
41 papers · 25.4k indexed · 3 hit papers · h-index 24

Bret Larget

40 papers receiving 24.9k citations

Hit Papers

MrBayes 3.2: Efficient Bayesian Phylogenetic...20.9k19992026200820175.0k10.0k15.0k20.0k

Peers

Bret Larget
Comparison fields: 5 of 173
  • Ecology, Evolution, Behavior and Systematics 7.9k
  • Paleontology 2.6k
  • Ecology 6.8k
  • Ecological Modeling 1.0k
  • Genetics 6.1k
Replace Liang Liu with:
Liang Liu United States
Paul van der Mark Netherlands
Aaron E. Darling Australia
Daniel L. Ayres United States
Maxim Teslenko Sweden
Sebastian Höhna Germany
Stéphane Guindon France
Olivier Gascuel France
David L. Swofford United States
Heiko A. Schmidt Austria
Bret Larget relative to Liang Liu United States Liang Liu's profile →
Citations per field
00.5×1.5×
Liang Liu · 1×
Citations per year

Countries citing papers authored by Bret Larget

Since Specialization
Citations

This map shows the geographic impact of Bret Larget's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bret Larget with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bret Larget more than expected).

Fields of papers citing papers by Bret Larget

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bret Larget. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bret Larget. The network helps show where Bret Larget may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Bret Larget, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bret Larget Line = papers co-authored together Bret Larget links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20234
2 201715
3 20174
4 201621
5 201631
6 201567
7 201429
8
MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Spacebreakdown →
201220931
9 20116
10 201148
11 201032
12 2010318
13 200978
14 20094
15 200727
16 200523
17 200449
18
Potential Applications and Pitfalls of Bayesian Inference of Phylogenybreakdown →
2002683
19 2000108
20 1999390

About Bret Larget

Bret Larget is a scholar working on Paleontology, Genetics, Developmental Biology, Nature and Landscape Conservation and Molecular Biology, having authored 41 papers that have together received 25.4k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (21 papers), Genetic diversity and population structure (18 papers), Bayesian Methods and Mixture Models (7 papers), Evolution and Paleontology Studies (7 papers), Genome Rearrangement Algorithms (4 papers), Genetic Mapping and Diversity in Plants and Animals (3 papers), Plant and animal studies (3 papers) and Evolution and Genetic Dynamics (3 papers). The work is most often cited by research in Ecology, Evolution, Behavior and Systematics (7.9k citations), Paleontology (2.6k citations), Ecology (6.8k citations), Ecological Modeling (1.0k citations) and Genetics (6.1k citations). Bret Larget has collaborated with scholars based in United States, Sweden and Canada. Frequent co-authors include John P. Huelsenbeck, Fredrik Ronquist, Paul van der Mark, Sebastian Höhna, Marc A. Suchard, Daniel L. Ayres, Aaron E. Darling, Liang Liu, Maxim Teslenko and Richard E. Miller. Their work appears in journals such as Systematic Biology, Evolution, Applied and Environmental Microbiology, Molecular Biology and Evolution and Journal of Applied Probability.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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