John R. Lamb
Impact in
- Genetics top 2%
- Genetic Mapping and Diversity in Plants and Animals
- Genetic Associations and Epidemiology
- Genetic and phenotypic traits in livestock
- Cancer Research top 5%
Papers in
-
- Bioinformatics and Genomic Networks 11
- Gene expression and cancer classification 5
- Gene Regulatory Network Analysis 4
- DNA Repair Mechanisms 3
- Genetics 11
- Genetic Associations and Epidemiology 5
- Co-authors
- Eric E. Schadt (11 shared papers)Mao Mao (5 shared papers)Aldons J. Lusis (3 shared papers)Roland Stoughton (2 shared papers)Stephen Friend (2 shared papers)Thomas A. Drake (2 shared papers)Stephanie A. Monks (1 shared paper)Thomas G. Ruff (1 shared paper)
- Journals
- The Journal of Immunology (6 papers)Nature Communications (3 papers)Diabetes (2 papers)Nature (2 papers)BMC Cancer (2 papers)
- Partner nations
- United StatesUnited KingdomIceland
In The Last Decade
John R. Lamb
42 papers receiving 3.7k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Genetics 1.1k
- Cancer Research 502
- Molecular Biology 2.1k
- Immunology 633
- Aging 44
Countries citing papers authored by John R. Lamb
This map shows the geographic impact of John R. Lamb'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 R. Lamb with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John R. Lamb more than expected).
Fields of papers citing papers by John R. Lamb
This network shows the impact of papers produced by John R. Lamb. 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 R. Lamb. The network helps show where John R. Lamb may publish in the future.
Co-authors
The 25 scholars most cited alongside John R. Lamb, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Genetics of gene expression surveyed in maize, mouse and man Hit paper breakdown → | 2003 | 1105 |
| 2 | 2005 | 207 | |
| 3 | 2005 | 181 | |
| 4 | 2014 | 181 | |
| 5 | 2005 | 168 | |
| 6 | 2010 | 165 | |
| 7 | 2004 | 147 | |
| 8 | 2009 | 145 | |
| 9 | 2014 | 138 | |
| 10 | 1990 | 114 | |
| 11 | 2009 | 107 | |
| 12 | 2022 | 106 | |
| 13 | 2009 | 101 | |
| 14 | 1991 | 99 | |
| 15 | 2018 | 70 | |
| 16 | 2020 | 69 | |
| 17 | 2006 | 66 | |
| 18 | 2012 | 65 | |
| 19 | 1994 | 56 | |
| 20 | 2011 | 46 |
About John R. Lamb
John R. Lamb is a scholar working on Molecular Biology, Genetics, Immunology, Cancer Research and Physiology, having authored 42 papers that have together received 3.8k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (11 papers), Genetic Associations and Epidemiology (5 papers), Adipose Tissue and Metabolism (5 papers), Gene expression and cancer classification (5 papers), T-cell and B-cell Immunology (4 papers), Gene Regulatory Network Analysis (4 papers), Cancer Genomics and Diagnostics (3 papers) and DNA Repair Mechanisms (3 papers). The work is most often cited by research in Genetics (1.1k citations), Cancer Research (502 citations), Molecular Biology (2.1k citations), Immunology (633 citations) and Aging (44 citations). John R. Lamb has collaborated with scholars based in United States, United Kingdom and Iceland. Frequent co-authors include Eric E. Schadt, Mao Mao, Aldons J. Lusis, Roland Stoughton, Stephen Friend, Thomas A. Drake, Stephanie A. Monks, Thomas G. Ruff, Nam Che and Peter S. Linsley. Their work appears in journals such as The Journal of Immunology, Nature Communications, Diabetes, Nature and BMC Cancer.
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.