John Garner
Impact in
- Genetics top 0.2%
- Genetic Associations and Epidemiology
- Forensic and Genetic Research
- Genomics and Rare Diseases
- Genomic variations and chromosomal abnormalities
- Genetic diversity and population structure
- Pharmacology top 1%
- Pharmacogenetics and Drug Metabolism
Papers in
- Genetics 6
- Genomic variations and chromosomal abnormalities 4
- Genetic Associations and Epidemiology 2
- Genomics and Rare Diseases 1
- Forensic and Genetic Research 1
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- Bioinformatics and Genomic Networks 2
- Biomedical Text Mining and Ontologies 1
- Co-authors
- Kevin G. Becker (2 shared papers)Supriyo De (2 shared papers)John R. Lopez (3 shared papers)Yonqing Zhang (1 shared paper)Justin E. Paschall (2 shared papers)Deanna M. Church (2 shared papers)Ilkka Lappalainen (2 shared papers)Paul Flicek (2 shared papers)
- Journals
- Nature Communications (1 paper)F1000Research (1 paper)Nature Genetics (1 paper)Nature (1 paper)Physiological Genomics (1 paper)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
John Garner
7 papers receiving 13.4k citations
John Garner's Hit Papers
Peers
Comparison fields: 5 of 155
- Genetics 7.2k
- Pharmacology 425
- Molecular Biology 2.5k
- Cancer Research 524
- Psychiatry and Mental health 606
Countries citing papers authored by John Garner
This map shows the geographic impact of John Garner'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 John Garner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Garner more than expected).
Fields of papers citing papers by John Garner
This network shows the impact of papers produced by John Garner. 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 John Garner. The network helps show where John Garner may publish in the future.
Co-authors
The 25 scholars most cited alongside John Garner, 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 | A global reference for human genetic variation Hit paper breakdown → | 2015 | 12887 |
| 2 | 2014 | 328 | |
| 3 | 2012 | 215 | |
| 4 | 2010 | 117 | |
| 5 | 2010 | 54 | |
| 6 | 2016 | 17 | |
| 7 | 2010 | 16 | |
| 8 | An integrated map of structural variation in 2,504 human genomes_supplement | 2016 | 1 |
About John Garner
John Garner is a scholar working on Genetics, Molecular Biology, Nuclear Energy and Engineering, Waste Management and Disposal and Infectious Diseases, having authored 8 papers that have together received 13.6k indexed citations. Recurring topics across this work include Genomic variations and chromosomal abnormalities (4 papers), Genetic Associations and Epidemiology (2 papers), Bioinformatics and Genomic Networks (2 papers), Genomics and Rare Diseases (1 paper), Forensic and Genetic Research (1 paper) and Biomedical Text Mining and Ontologies (1 paper). The work is most often cited by research in Genetics (7.2k citations), Pharmacology (425 citations), Molecular Biology (2.5k citations), Cancer Research (524 citations) and Psychiatry and Mental health (606 citations). John Garner has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Kevin G. Becker, Supriyo De, John R. Lopez, Yonqing Zhang, Justin E. Paschall, Deanna M. Church, Ilkka Lappalainen, Paul Flicek, Chao Chen and George Zhou. Their work appears in journals such as Nature Communications, F1000Research, Nature Genetics, Nature and Physiological Genomics.
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.