R R Williams

1.2k citations
13 papers · 1.0k indexed · h-index 13

R R Williams

13 papers receiving 982 citations

Peers

R R Williams
Comparison fields: 5 of 76
  • Endocrinology, Diabetes and Metabolism 501
  • Cardiology and Cardiovascular Medicine 467
  • Nephrology 89
  • Surgery 295
  • Genetics 156
Replace A Teuscher with:
A Teuscher Switzerland
J. C. Smith United Kingdom
Robert W. Stout United Kingdom
D. Wile United Kingdom
A. C. Asmal South Africa
Hiroshi Hirose Japan
Roberto S. Cunha Brazil
E Knapp Austria
Z Fejfar Czechia
M. M. S. Ahuja India
R R Williams relative to A Teuscher Switzerland A Teuscher's profile →
Citations per field
00.5×1.6×
A Teuscher · 1×
Citations per year

Countries citing papers authored by R R Williams

Since Specialization
Citations

This map shows the geographic impact of R R 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 R R Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites R R Williams more than expected).

Fields of papers citing papers by R R Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R R 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 R R Williams. The network helps show where R R Williams may publish in the future.

Co-authorship network

The 25 scholars most cited alongside R R 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 R R Williams Line = papers co-authored together R R Williams links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 199518
2
Tabulations and expectations regarding the genetics of human hypertension.
199432
3 199329
4 1991104
5 1991130
6 199148
7 199159
8 1990140
9 1990115
10 198947
11 1988238
12
A DNA probe for the LDL receptor gene is tightly linked to hypercholesterolemia in a pedigree with early coronary disease.
198630
13 198117

About R R Williams

R R Williams is a scholar working on Cancer Research, Pharmacy, Endocrinology, Diabetes and Metabolism, Cardiology and Cardiovascular Medicine and Genetics, having authored 13 papers that have together received 1.0k indexed citations. Recurring topics across this work include Cancer, Lipids, and Metabolism (4 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers), Lipid metabolism and disorders (3 papers), Lipoproteins and Cardiovascular Health (3 papers), Diabetes and associated disorders (2 papers), Nutrition, Genetics, and Disease (1 paper), Cholesterol and Lipid Metabolism (1 paper) and Coagulation, Bradykinin, Polyphosphates, and Angioedema (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (501 citations), Cardiology and Cardiovascular Medicine (467 citations), Nephrology (89 citations), Surgery (295 citations) and Genetics (156 citations). R R Williams has collaborated with scholars based in United States and Belgium. Frequent co-authors include P N Hopkins, S C Hunt, Jean-Marc Lalouel, Susan Stephenson, Lianjun Wu, M. Emi, Per‐Henrik Iverius, Akira Hata, Daniel E. Wilson and Sandra J. Hasstedt. Their work appears in journals such as Hypertension, JAMA, Ophthalmology, Journal of Biological Chemistry and American Journal of Clinical Nutrition.

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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