Neil D. Evans
- Molecular Biology
- Hematology top 5%
- Oncology
- Modeling and Simulation top 2%
- Control and Systems Engineering top 10%
- Co-authors
- Michael J. ChappellK.R. GodfreyA.R. BradwellJohn HattersleyColin A. HutchisonPaul CockwellMark CookJames Yates
- Topics
- Cancer therapeutics and mechanisms (8 papers)COVID-19 epidemiological studies (8 papers)Gene Regulatory Network Analysis (8 papers)
- Journals
- Journal of the American Chemical SocietySHILAP Revista de lepidopterologíaThe EMBO Journal
- Partner nations
- United KingdomSwedenUnited States
In The Last Decade
Neil D. Evans
92 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 154
- Molecular Biology 647
- Hematology 281
- Oncology 170
- Modeling and Simulation 130
- Control and Systems Engineering 123
Countries citing papers authored by Neil D. Evans
This map shows the geographic impact of Neil D. Evans'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 Neil D. Evans with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Neil D. Evans more than expected).
Fields of papers citing papers by Neil D. Evans
This network shows the impact of papers produced by Neil D. Evans. 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 Neil D. Evans. The network helps show where Neil D. Evans may publish in the future.
Co-authorship network of co-authors of Neil D. Evans
This figure shows the co-authorship network connecting the top 25 collaborators of Neil D. Evans. A scholar is included among the top collaborators of Neil D. Evans 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 Neil D. Evans. Neil D. Evans is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 23 | |
| 6 | 18 | |
| 7 | 8 | |
| 8 | 3 | |
| 9 | 37 | |
| 10 | 17 | |
| 11 | 6 | |
| 12 | 14 | |
| 13 | 28 | |
| 14 | 5 | |
| 15 | 17 | |
| 16 | 24 | |
| 17 | 71 | |
| 18 | Towards the Formal Verification of a Java Processor in Event-B. | 2 |
| 19 | A Proposal for Records in Event-B | 1 |
| 20 | 17 |
About Neil D. Evans
Neil D. Evans is a scholar working on Modeling and Simulation, Hardware and Architecture and Computational Theory and Mathematics, having authored 97 papers that have together received 1.5k indexed citations. Recurring topics across this work include Cancer therapeutics and mechanisms (8 papers), COVID-19 epidemiological studies (8 papers) and Gene Regulatory Network Analysis (8 papers). The work is most often cited by research in Modeling and Simulation (130 citations), Hematology (281 citations) and Nephrology (94 citations). Neil D. Evans has collaborated with scholars based in United Kingdom, Sweden and United States. Frequent co-authors include Michael J. Chappell, K.R. Godfrey, A.R. Bradwell, John Hattersley, Colin A. Hutchison, Paul Cockwell, Mark Cook, James Yates, Michael J. Chapman and Graham P. Mead. Their work appears in journals such as Journal of the American Chemical Society, SHILAP Revista de lepidopterología and The EMBO Journal.
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.