John J. Tanner
Impact in
- Biochemistry top 0.5%
- Amino Acid Enzymes and Metabolism
- Structural Biology top 2%
Papers in
-
- Biochemical and Molecular Research 37
- Protein Structure and Dynamics 29
- DNA and Nucleic Acid Chemistry 10
-
- Enzyme Structure and Function 96
- Co-authors
- Donald Becker (45 shared papers)Jianlin Cheng (7 shared papers)Michael T. Henzl (24 shared papers)Kurt L. Krause (8 shared papers)Paul E. Smith (4 shared papers)Christopher A. Bottoms (6 shared papers)Pablo Sobrado (20 shared papers)Jonathan P. Schuermann (13 shared papers)
- Journals
- Biochemistry (35 papers)Journal of Biological Chemistry (15 papers)Archives of Biochemistry and Biophysics (14 papers)Journal of Molecular Biology (13 papers)Protein Science (11 papers)
- Partner nations
- United StatesIndiaPoland
In The Last Decade
John J. Tanner
171 papers receiving 4.6k citations
Peers
Comparison fields: 5 of 146
- Biochemistry 504
- Structural Biology 78
- Molecular Biology 3.0k
- Clinical Biochemistry 247
- Virology 150
Countries citing papers authored by John J. Tanner
This map shows the geographic impact of John J. Tanner'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 J. Tanner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John J. Tanner more than expected).
Fields of papers citing papers by John J. Tanner
This network shows the impact of papers produced by John J. Tanner. 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 J. Tanner. The network helps show where John J. Tanner may publish in the future.
Co-authors
The 25 scholars most cited alongside John J. Tanner, 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 174 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 202 | |
| 2 | 2020 | 190 | |
| 3 | 1996 | 175 | |
| 4 | 2021 | 166 | |
| 5 | 2010 | 134 | |
| 6 | 2002 | 130 | |
| 7 | 2018 | 120 | |
| 8 | 2008 | 119 | |
| 9 | 2006 | 110 | |
| 10 | 2003 | 90 | |
| 11 | 2007 | 84 | |
| 12 | 1996 | 80 | |
| 13 | 2004 | 67 | |
| 14 | 2011 | 66 | |
| 15 | 2017 | 63 | |
| 16 | 1990 | 63 | |
| 17 | 2014 | 61 | |
| 18 | 2012 | 59 | |
| 19 | 2010 | 55 | |
| 20 | 1992 | 55 |
About John J. Tanner
John J. Tanner is a scholar working on Molecular Biology, Materials Chemistry, Biochemistry, Clinical Biochemistry and Genetics, having authored 174 papers that have together received 4.7k indexed citations. Recurring topics across this work include Enzyme Structure and Function (96 papers), Biochemical and Molecular Research (37 papers), Protein Structure and Dynamics (29 papers), Amino Acid Enzymes and Metabolism (25 papers), Metabolism and Genetic Disorders (20 papers), Bacterial Genetics and Biotechnology (14 papers), Cancer, Hypoxia, and Metabolism (12 papers) and DNA and Nucleic Acid Chemistry (10 papers). The work is most often cited by research in Biochemistry (504 citations), Structural Biology (78 citations), Molecular Biology (3.0k citations), Clinical Biochemistry (247 citations) and Virology (150 citations). John J. Tanner has collaborated with scholars based in United States, India and Poland. Frequent co-authors include Donald Becker, Jianlin Cheng, Michael T. Henzl, Kurt L. Krause, Paul E. Smith, Christopher A. Bottoms, Pablo Sobrado, Jonathan P. Schuermann, Jermaine L. Jenkins and Min Luo. Their work appears in journals such as Biochemistry, Journal of Biological Chemistry, Archives of Biochemistry and Biophysics, Journal of Molecular Biology and Protein Science.
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.