Jordan Hoffmann
Impact in
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- Electrostatics and Colloid Interactions
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- Gamma-ray bursts and supernovae
- Astrophysical Phenomena and Observations
- Pulsars and Gravitational Waves Research
Papers in
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- Protein Structure and Dynamics 3
- RNA and protein synthesis mechanisms 2
- Machine Learning in Bioinformatics 1
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- Tree Root and Stability Studies 2
- Co-authors
- Dirk Gillespie (1 shared paper)Seth Donoughe (2 shared papers)Chris H. Rycroft (2 shared papers)L. Mahadevan (1 shared paper)Lisa M. Lee (1 shared paper)Shmuel M. Rubinstein (1 shared paper)Yohai Bar‐Sinai (1 shared paper)Debahuti Mishra (1 shared paper)
- Journals
- Biophysical Journal (2 papers)Biology Open (1 paper)Proceedings of the National Academy of Sciences (1 paper)Proteins Structure Function and Bioinformatics (1 paper)Science Advances (1 paper)
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
Jordan Hoffmann
11 papers receiving 224 citations
Peers
Comparison fields: 5 of 94
- Physical and Theoretical Chemistry 25
- Astronomy and Astrophysics 44
- Ecological Modeling 7
- Nuclear and High Energy Physics 19
- Architecture 2
Countries citing papers authored by Jordan Hoffmann
This map shows the geographic impact of Jordan Hoffmann'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 Jordan Hoffmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jordan Hoffmann more than expected).
Fields of papers citing papers by Jordan Hoffmann
This network shows the impact of papers produced by Jordan Hoffmann. 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 Jordan Hoffmann. The network helps show where Jordan Hoffmann may publish in the future.
Co-authors
The 25 scholars most cited alongside Jordan Hoffmann, 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 | 2013 | 47 | |
| 2 | 2019 | 45 | |
| 3 | 2022 | 43 | |
| 4 | 2019 | 35 | |
| 5 | 2018 | 35 | |
| 6 | 2022 | 16 | |
| 7 | 2016 | 11 | |
| 8 | 2014 | 4 | |
| 9 | 2019 | 1 | |
| 10 | 2013 | 1 | |
| 11 | 1996 | 1 | |
| 12 | 2022 | 0 | |
| 13 | 2014 | 0 |
About Jordan Hoffmann
Jordan Hoffmann is a scholar working on Molecular Biology, Mechanical Engineering, Astronomy and Astrophysics, Atomic and Molecular Physics, and Optics and Nuclear and High Energy Physics, having authored 13 papers that have together received 239 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (3 papers), RNA and protein synthesis mechanisms (2 papers), Tree Root and Stability Studies (2 papers), Machine Learning in Bioinformatics (1 paper), Natural Language Processing Techniques (1 paper), Molecular spectroscopy and chirality (1 paper), Particle Detector Development and Performance (1 paper) and Radiation Detection and Scintillator Technologies (1 paper). The work is most often cited by research in Physical and Theoretical Chemistry (25 citations), Astronomy and Astrophysics (44 citations), Ecological Modeling (7 citations), Nuclear and High Energy Physics (19 citations) and Architecture (2 citations). Jordan Hoffmann has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Dirk Gillespie, Seth Donoughe, Chris H. Rycroft, L. Mahadevan, Lisa M. Lee, Shmuel M. Rubinstein, Yohai Bar‐Sinai, Debahuti Mishra, A J Goodwin and Lin Yan. Their work appears in journals such as Biophysical Journal, Biology Open, Proceedings of the National Academy of Sciences, Proteins Structure Function and Bioinformatics and Science Advances.
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.