William King

12 papers receiving 1.3k citations

William King's Hit Papers

Monoclonal antibodies localize oestrogen receptor in the nuclei of target cells 1984 · 1.1k citations
1.1k0+14+28Years since publication2505007501000

Peers

William King
Comparison fields: 5 of 109
  • Genetics 729
  • Behavioral Neuroscience 72
  • Periodontics 75
  • Reproductive Medicine 131
  • Endocrinology, Diabetes and Metabolism 241
Replace Naohiro Fujimoto with:
Naohiro Fujimoto Japan
Lorraine I. McKay United States
Angyi Lin United States
Steven Lehrer United States
Sandra Regiani United States
Padma Maruvada United States
P. C. MacDonald United States
Ebru Karpuzoglu United States
Bengt G. Johansson Sweden
Balakrishna L. Lokeshwar United States
William King relative to Naohiro Fujimoto Japan Naohiro Fujimoto's profile →
Citations per field
00.5×3.6×
Naohiro Fujimoto · 1×
Citations per year

Countries citing papers authored by William King

Since Specialization
Citations

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

Fields of papers citing papers by William King

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1
Monoclonal antibodies localize oestrogen receptor in the nuclei of target cells
Hit paper breakdown →
19841136
2 200551
3 199645
4 199843
5 198330
6 196929
7 198916
8 19805
9 19705
10 19844
11 20242
12 20242
13 20250

About William King

William King is a scholar working on Periodontics, Molecular Biology, Epidemiology, General Dentistry and Public Health, Environmental and Occupational Health, having authored 13 papers that have together received 1.4k indexed citations. Recurring topics across this work include Oral microbiology and periodontitis research (5 papers), Dental Research and COVID-19 (2 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), Urinary Tract Infections Management (2 papers), Estrogen and related hormone effects (1 paper), Venous Thromboembolism Diagnosis and Management (1 paper), Injury Epidemiology and Prevention (1 paper) and Streptococcal Infections and Treatments (1 paper). The work is most often cited by research in Genetics (729 citations), Behavioral Neuroscience (72 citations), Periodontics (75 citations), Reproductive Medicine (131 citations) and Endocrinology, Diabetes and Metabolism (241 citations). William King has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Geoffrey L. Greene, E. G. Black, Margaret C. Eggo, Michael C. Sheppard, A R Volpe, Cynthia L. Fowler, Clair E. Cox, Richard E. Stallard, Ira Klimberg and I B Pless. Their work appears in journals such as Journal of Periodontology, Journal of Public Health Dentistry, The Journal of Clinical Endocrinology & Metabolism, Nature and Journal of Periodontal Research.

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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