Gavin Huttley
Impact in
- Virology top 0.2%
- HIV Research and Treatment
- Immunology top 1%
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
Papers in
- Genetics 27
- Genetic diversity and population structure 9
- Evolution and Genetic Dynamics 5
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- Genomics and Phylogenetic Studies 32
- RNA and protein synthesis mechanisms 11
- Genomics and Chromatin Dynamics 9
- Gene expression and cancer classification 5
- Epigenetics and DNA Methylation 5
- Co-authors
- Benjamin D. KaehlerJ. Gregory CaporasoNicholas A. BokulichRob KnightMatthew R. DillonEvan BolyenJai Ram RideoutMary Carrington
- Journals
- Molecular Biology and Evolution (6 papers)Genetics (5 papers)PLoS ONE (5 papers)BMC Bioinformatics (4 papers)Nature Communications (2 papers)
- Partner nations
- AustraliaUnited StatesSingapore
In The Last Decade
Gavin Huttley
62 papers receiving 9.6k citations
Hit Papers
Peers
Comparison fields: 5 of 191
- Virology 2.1k
- Immunology 2.2k
- Infectious Diseases 1.4k
- Ecology 1.4k
- Molecular Biology 3.7k
Countries citing papers authored by Gavin Huttley
This map shows the geographic impact of Gavin Huttley'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 Gavin Huttley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gavin Huttley more than expected).
Fields of papers citing papers by Gavin Huttley
This network shows the impact of papers produced by Gavin Huttley. 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 Gavin Huttley. The network helps show where Gavin Huttley may publish in the future.
Co-authors
The 25 scholars most cited alongside Gavin Huttley, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2020 | 6 | |
| 3 | 2020 | 4 | |
| 4 | 2019 | 126 | |
| 5 | 2018 | 54 | |
| 6 | 2017 | 7 | |
| 7 | 2016 | 51 | |
| 8 | 2015 | 27 | |
| 9 | 2013 | 49 | |
| 10 | 2012 | 93 | |
| 11 | 2012 | 74 | |
| 12 | 2011 | 83 | |
| 13 | 2011 | 9 | |
| 14 | 2009 | 23 | |
| 15 | 2008 | 24 | |
| 16 | 2008 | 7 | |
| 17 | 2007 | 30 | |
| 18 | PyEvolve: a toolkit for statistical modelling of molecular evolution Hit paper breakdown → | 2004 | 515 |
| 19 | 2002 | 33 | |
| 20 | 2001 | 33 |
About Gavin Huttley
Gavin Huttley is a scholar working on Genetics, Molecular Biology, Virology, Behavioral Neuroscience and Paleontology, having authored 65 papers that have together received 9.8k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (32 papers), RNA and protein synthesis mechanisms (11 papers), Genomics and Chromatin Dynamics (9 papers), Genetic diversity and population structure (9 papers), Chromosomal and Genetic Variations (7 papers), Gene expression and cancer classification (5 papers), Epigenetics and DNA Methylation (5 papers) and Evolution and Genetic Dynamics (5 papers). The work is most often cited by research in Virology (2.1k citations), Immunology (2.2k citations), Infectious Diseases (1.4k citations), Ecology (1.4k citations) and Molecular Biology (3.7k citations). Gavin Huttley has collaborated with scholars based in Australia, United States and Singapore. Frequent co-authors include Benjamin D. Kaehler, J. Gregory Caporaso, Nicholas A. Bokulich, Rob Knight, Matthew R. Dillon, Evan Bolyen, Jai Ram Rideout, Mary Carrington, Stephen J. O’Brien and Eric Vittinghoff. Their work appears in journals such as Molecular Biology and Evolution, Genetics, PLoS ONE, BMC Bioinformatics and Nature Communications.
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.