Daniel Kahn
Impact in
- Biochemistry top 10%
- Amino Acid Enzymes and Metabolism
- Pollution top 10%
- Wastewater Treatment and Nitrogen Removal
Papers in
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- Protein Structure and Dynamics 3
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- Hemoglobin structure and function 3
- Co-authors
- Hans V. Westerhoff (8 shared papers)Wally C. van Heeswijk (2 shared papers)Sjouke Hoving (2 shared papers)Douwe Molenaar (2 shared papers)Jeanne M. E. Jacobs (1 shared paper)M. David (1 shared paper)Jacques Batut (1 shared paper)Marie‐Line Daveran‐Mingot (1 shared paper)
- Journals
- Genes & Development (1 paper)Molecular Microbiology (1 paper)The EMBO Journal (1 paper)Antonie van Leeuwenhoek (1 paper)Bioinformatics (1 paper)
- Partner nations
- NetherlandsFranceUnited Kingdom
In The Last Decade
Daniel Kahn
13 papers receiving 668 citations
Peers
Comparison fields: 5 of 80
- Biochemistry 73
- Pollution 91
- Molecular Biology 419
- Genetics 164
- Plant Science 200
Countries citing papers authored by Daniel Kahn
This map shows the geographic impact of Daniel Kahn'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 Daniel Kahn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Kahn more than expected).
Fields of papers citing papers by Daniel Kahn
This network shows the impact of papers produced by Daniel Kahn. 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 Daniel Kahn. The network helps show where Daniel Kahn may publish in the future.
Co-authors
The 23 scholars most cited alongside Daniel Kahn, 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 | 1996 | 171 | |
| 2 | 1989 | 171 | |
| 3 | 1991 | 114 | |
| 4 | 1993 | 74 | |
| 5 | 1995 | 52 | |
| 6 | 1997 | 36 | |
| 7 | 1999 | 19 | |
| 8 | 1993 | 11 | |
| 9 | 1965 | 11 | |
| 10 | 1991 | 10 | |
| 11 | 1992 | 10 | |
| 12 | The use of large text corpora for evaluating text-to-speech systems | 1998 | 4 |
| 13 | 1995 | 3 | |
| 14 | 1981 | 1 |
About Daniel Kahn
Daniel Kahn is a scholar working on Molecular Biology, Cell Biology, Artificial Intelligence, Physical and Theoretical Chemistry and Spectroscopy, having authored 14 papers that have together received 687 indexed citations. Recurring topics across this work include Hemoglobin structure and function (3 papers), Protein Structure and Dynamics (3 papers), Plant nutrient uptake and metabolism (2 papers), Legume Nitrogen Fixing Symbiosis (2 papers), Speech and dialogue systems (2 papers), Amino Acid Enzymes and Metabolism (2 papers), thermodynamics and calorimetric analyses (2 papers) and Mass Spectrometry Techniques and Applications (2 papers). The work is most often cited by research in Biochemistry (73 citations), Pollution (91 citations), Molecular Biology (419 citations), Genetics (164 citations) and Plant Science (200 citations). Daniel Kahn has collaborated with scholars based in Netherlands, France and United Kingdom. Frequent co-authors include Hans V. Westerhoff, Wally C. van Heeswijk, Sjouke Hoving, Douwe Molenaar, Jeanne M. E. Jacobs, M. David, Jacques Batut, Marie‐Line Daveran‐Mingot, Stefan Schuster and Jérôme Gouzy. Their work appears in journals such as Genes & Development, Molecular Microbiology, The EMBO Journal, Antonie van Leeuwenhoek and Bioinformatics.
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.