David J. Wales
- Materials Chemistry top 0.2%
- Atomic and Molecular Physics, and Optics top 0.1%
- Molecular Biology top 1%
- Atmospheric Science top 0.5%
- Organic Chemistry top 0.5%
- Co-authors
- Jonathan P. K. DoyeAnthony J. StoneHarold A. ScheragaR. Stephen BerryMark A. MillerTiffany R. WalshMatthew P. HodgesLindsey J. Munro
- Topics
- Advanced Chemical Physics Studies (169 papers)Protein Structure and Dynamics (106 papers)Spectroscopy and Quantum Chemical Studies (97 papers)
- Cited by
- Atomic and Molecular Physics, and OpticsMaterials ChemistryStatistical and Nonlinear Physics
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
David J. Wales
463 papers receiving 21.0k citations
Hit Papers
Peers
Comparison fields: 5 of 195
- Materials Chemistry 9.9k
- Atomic and Molecular Physics, and Optics 9.2k
- Molecular Biology 5.0k
- Atmospheric Science 3.1k
- Organic Chemistry 2.4k
Countries citing papers authored by David J. Wales
This map shows the geographic impact of David J. Wales'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 David J. Wales with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David J. Wales more than expected).
Fields of papers citing papers by David J. Wales
This network shows the impact of papers produced by David J. Wales. 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 David J. Wales. The network helps show where David J. Wales may publish in the future.
Co-authorship network of co-authors of David J. Wales
This figure shows the co-authorship network connecting the top 25 collaborators of David J. Wales. A scholar is included among the top collaborators of David J. Wales based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David J. Wales. David J. Wales is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 6 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 6 | |
| 9 | 4 | |
| 10 | 4 | |
| 11 | 17 | |
| 12 | 5 | |
| 13 | 4 | |
| 14 | 11 | |
| 15 | 72 | |
| 16 | 19 | |
| 17 | Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approachbreakdown → | 339 |
| 18 | 10 | |
| 19 | 10 | |
| 20 | 21 |
About David J. Wales
David J. Wales is a scholar working on Atomic and Molecular Physics, and Optics, Statistical and Nonlinear Physics and Physical and Theoretical Chemistry, having authored 477 papers that have together received 22.5k indexed citations. Recurring topics across this work include Advanced Chemical Physics Studies (169 papers), Protein Structure and Dynamics (106 papers) and Spectroscopy and Quantum Chemical Studies (97 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (9.2k citations), Materials Chemistry (9.9k citations) and Statistical and Nonlinear Physics (2.2k citations). David J. Wales has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Jonathan P. K. Doye, Anthony J. Stone, Harold A. Scheraga, R. Stephen Berry, Mark A. Miller, Tiffany R. Walsh, Matthew P. Hodges, Lindsey J. Munro, David A. Evans and J. Hernández‐Rojas. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
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.