Jack Kamm
Impact in
- Genetics top 5%
- Genetic diversity and population structure
- Forensic and Genetic Research
- Genetic and phenotypic traits in livestock
- Genetic Mapping and Diversity in Plants and Animals
- Evolution and Genetic Dynamics
- Paleontology top 10%
- Archaeology and ancient environmental studies
Papers in ⓘ
- Genetics 8
- Genetic diversity and population structure 5
- Forensic and Genetic Research 4
- Evolution and Genetic Dynamics 2
- Genetic Mapping and Diversity in Plants and Animals 2
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- SARS-CoV-2 and COVID-19 Research 3
- SARS-CoV-2 detection and testing 2
- Viral gastroenteritis research and epidemiology 2
- Co-authors
- Yun S. Song (9 shared papers)Jonathan Terhorst (3 shared papers)Jeffrey P. Spence (3 shared papers)Richard Durbin (1 shared paper)Matthias Steinrücken (2 shared papers)J. Víctor Moreno-Mayar (1 shared paper)Joshua D. Reuther (1 shared paper)Martin Sikora (1 shared paper)
- Journals
- Advances in Applied Probability (2 papers)Transfusion (1 paper)Nature Genetics (1 paper)Molecular Ecology (1 paper)Genetics (1 paper)
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
Jack Kamm
15 papers receiving 940 citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Genetics 630
- Paleontology 92
- Anthropology 82
- Ecological Modeling 32
- Archeology 72
Countries citing papers authored by Jack Kamm
This map shows the geographic impact of Jack Kamm'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 Jack Kamm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jack Kamm more than expected).
Fields of papers citing papers by Jack Kamm
This network shows the impact of papers produced by Jack Kamm. 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 Jack Kamm. The network helps show where Jack Kamm may publish in the future.
Co-authors
The 25 scholars most cited alongside Jack Kamm, 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 | Robust and scalable inference of population history from hundreds of unphased whole genomes Hit paper breakdown → | 2016 | 489 |
| 2 | 2018 | 176 | |
| 3 | 2019 | 89 | |
| 4 | 2018 | 43 | |
| 5 | 2019 | 38 | |
| 6 | 2020 | 26 | |
| 7 | 2016 | 24 | |
| 8 | 2020 | 18 | |
| 9 | 2022 | 10 | |
| 10 | 2012 | 9 | |
| 11 | 2022 | 9 | |
| 12 | 2012 | 7 | |
| 13 | 2014 | 6 | |
| 14 | 2022 | 6 | |
| 15 | 2020 | 1 |
About Jack Kamm
Jack Kamm is a scholar working on Genetics, Infectious Diseases, Molecular Medicine, Clinical Biochemistry and Paleontology, having authored 15 papers that have together received 951 indexed citations. Recurring topics across this work include Genetic diversity and population structure (5 papers), Forensic and Genetic Research (4 papers), SARS-CoV-2 and COVID-19 Research (3 papers), SARS-CoV-2 detection and testing (2 papers), Viral gastroenteritis research and epidemiology (2 papers), Evolution and Genetic Dynamics (2 papers), Cancer Genomics and Diagnostics (2 papers) and Genetic Mapping and Diversity in Plants and Animals (2 papers). The work is most often cited by research in Genetics (630 citations), Paleontology (92 citations), Anthropology (82 citations), Ecological Modeling (32 citations) and Archeology (72 citations). Jack Kamm has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Yun S. Song, Jonathan Terhorst, Jeffrey P. Spence, Richard Durbin, Matthias Steinrücken, J. Víctor Moreno-Mayar, Joshua D. Reuther, Martin Sikora, Anna‐Sapfo Malaspinas and Lasse Vinner. Their work appears in journals such as Advances in Applied Probability, Transfusion, Nature Genetics, Molecular Ecology and Genetics.
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.