Dominic A. Clark
- Molecular Biology top 10%
- Computational Theory and Mathematics top 0.5%
- Materials Chemistry top 10%
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Co-authors
- Paul CzodrowskiJessica VamathevanIan DunhamShanrong ZhaoAnant MadabhushiGeorge LeeMichaela SpitzerEdgardo A. Ferrán
- Topics
- Machine Learning in Bioinformatics (5 papers)Genetics, Bioinformatics, and Biomedical Research (4 papers)Semantic Web and Ontologies (4 papers)
- Partner nations
- United KingdomFranceUnited States
In The Last Decade
Dominic A. Clark
23 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 179
- Molecular Biology 979
- Computational Theory and Mathematics 863
- Materials Chemistry 440
- Artificial Intelligence 371
- Radiology, Nuclear Medicine and Imaging 172
Countries citing papers authored by Dominic A. Clark
This map shows the geographic impact of Dominic A. Clark'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 Dominic A. Clark with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dominic A. Clark more than expected).
Fields of papers citing papers by Dominic A. Clark
This network shows the impact of papers produced by Dominic A. Clark. 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 Dominic A. Clark. The network helps show where Dominic A. Clark may publish in the future.
Co-authorship network of co-authors of Dominic A. Clark
This figure shows the co-authorship network connecting the top 25 collaborators of Dominic A. Clark. A scholar is included among the top collaborators of Dominic A. Clark 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 Dominic A. Clark. Dominic A. Clark is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | Applications of machine learning in drug discovery and developmentbreakdown → | 1696 |
| 3 | 55 | |
| 4 | 9 | |
| 5 | 16 | |
| 6 | 28 | |
| 7 | 28 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 12 | |
| 11 | Genetic map construction with constraints. | 4 |
| 12 | Inductive logic programming used to discover topological constraints in protein structures. | 4 |
| 13 | APPLAUSE: applications using the ElipSys parallel CLP system | 4 |
| 14 | Representing Uncertain Knowledge: An Artificial Intelligence Approach | 57 |
| 15 | 1 | |
| 16 | 58 | |
| 17 | 30 | |
| 18 | 10 | |
| 19 | 25 | |
| 20 | 5 |
About Dominic A. Clark
Dominic A. Clark is a scholar working on Artificial Intelligence, Software and History and Philosophy of Science, having authored 24 papers that have together received 2.1k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (5 papers), Genetics, Bioinformatics, and Biomedical Research (4 papers) and Semantic Web and Ontologies (4 papers). The work is most often cited by research in Health Informatics (96 citations), Computational Theory and Mathematics (863 citations) and General Decision Sciences (28 citations). Dominic A. Clark has collaborated with scholars based in United Kingdom, France and United States. Frequent co-authors include Paul Czodrowski, Jessica Vamathevan, Ian Dunham, Shanrong Zhao, Anant Madabhushi, George Lee, Michaela Spitzer, Edgardo A. Ferrán, Parantu K. Shah and Bin Li. Their work appears in journals such as Nature Reviews Drug Discovery, BMC Bioinformatics and Drug Discovery Today.
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.