Marc S. Williams
- Genetics top 0.5%
- Molecular Biology top 5%
- Public Health, Environmental and Occupational Health top 1%
- Pediatrics, Perinatology and Child Health top 1%
- Cancer Research top 2%
- Co-authors
- Heidi L. RehmRobert L. NussbaumMichael S. WatsonChrista Lese MartinLeslie G. BieseckerJonathan S. BergRobert C. GreenBruce R. Korf
- Topics
- Genomics and Rare Diseases (82 papers)BRCA gene mutations in cancer (60 papers)Health Systems, Economic Evaluations, Quality of Life (33 papers)
- Cited by
- GeneticsPharmacologyCancer Research
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Marc S. Williams
219 papers receiving 6.9k citations
Hit Papers
Peers
Comparison fields: 5 of 169
- Genetics 3.1k
- Molecular Biology 1.3k
- Public Health, Environmental and Occupational Health 1.2k
- Pediatrics, Perinatology and Child Health 888
- Cancer Research 854
Countries citing papers authored by Marc S. Williams
This map shows the geographic impact of Marc S. Williams'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 Marc S. Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc S. Williams more than expected).
Fields of papers citing papers by Marc S. Williams
This network shows the impact of papers produced by Marc S. Williams. 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 Marc S. Williams. The network helps show where Marc S. Williams may publish in the future.
Co-authorship network of co-authors of Marc S. Williams
This figure shows the co-authorship network connecting the top 25 collaborators of Marc S. Williams. A scholar is included among the top collaborators of Marc S. Williams 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 Marc S. Williams. Marc S. Williams is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 3 | |
| 3 | 7 | |
| 4 | 6 | |
| 5 | 1 | |
| 6 | 9 | |
| 7 | 3 | |
| 8 | 7 | |
| 9 | 11 | |
| 10 | 1 | |
| 11 | 4 | |
| 12 | 2 | |
| 13 | 2 | |
| 14 | 22 | |
| 15 | 15 | |
| 16 | 12 | |
| 17 | 116 | |
| 18 | 18 | |
| 19 | 56 | |
| 20 | 41 |
About Marc S. Williams
Marc S. Williams is a scholar working on Genetics, Health Information Management and Pathology and Forensic Medicine, having authored 227 papers that have together received 7.1k indexed citations. Recurring topics across this work include Genomics and Rare Diseases (82 papers), BRCA gene mutations in cancer (60 papers) and Health Systems, Economic Evaluations, Quality of Life (33 papers). The work is most often cited by research in Genetics (3.1k citations), Pharmacology (830 citations) and Cancer Research (854 citations). Marc S. Williams has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Heidi L. Rehm, Robert L. Nussbaum, Michael S. Watson, Christa Lese Martin, Leslie G. Biesecker, Jonathan S. Berg, Robert C. Green, Bruce R. Korf, Kelly E. Ormond and Wayne W. Grody. Their work appears in journals such as The Lancet, JAMA and Journal of Clinical Oncology.
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.