Marc S. Williams

19.4k citations
227 papers · 7.1k indexed · 3 hit papers · h-index 37

Marc S. Williams

219 papers receiving 6.9k citations

Hit Papers

Pharmacogenomics238201320262017202150010001.5k

Peers

Marc S. Williams
Comparison fields: 5 of 169
  • Genetics 3.1k
  • Pharmacology 830
  • Cancer Research 854
  • Pediatrics, Perinatology and Child Health 888
  • Genetics 466
Replace Wylie Burke with:
Wylie Burke United States
Muin J. Khoury United States
Amy L. McGuire United States
Michael S. Watson United States
Kelly E. Ormond United States
Kathryn J. Ruddy United States
Martina C. Cornel Netherlands
Timothy R. Rebbeck United States
Montserrat García‐Closas United States
Katherine Payne United Kingdom
Marc S. Williams relative to Wylie Burke United States Wylie Burke's profile →
Citations per field
00.5×
Wylie Burke · 1×
Citations per year

Countries citing papers authored by Marc S. Williams

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

The 25 scholars most cited alongside Marc S. Williams, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Marc S. Williams Line = papers co-authored together Marc S. Williams links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20255
2 20243
3 20237
4 20236
5 20231
6 20229
7 20223
8 20217
9 202111
10 20211
11 20204
12 20202
13 20172
14 201622
15 201615
16 201412
17 2011116
18 201118
19 201156
20 200941

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), Health Systems, Economic Evaluations, Quality of Life (33 papers), Genetic factors in colorectal cancer (31 papers), Ethics in Clinical Research (26 papers), Cancer Genomics and Diagnostics (21 papers), Biomedical Text Mining and Ontologies (19 papers) and Genomic variations and chromosomal abnormalities (14 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.

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