Charlene J. Williams

4.1k citations
64 papers · 3.2k indexed · 1 hit paper · h-index 28

Charlene J. Williams

63 papers receiving 3.1k citations

Hit Papers

Rat brain preproenkephalin mRNA. cDNA cloning, primary st...5061984202619982012100200300400500

Peers

Charlene J. Williams
Comparison fields: 5 of 130
  • Rheumatology 760
  • Immunology and Allergy 294
  • Endocrine and Autonomic Systems 279
  • Nephrology 273
  • Genetics 933
Replace Franz Rüschendorf with:
Franz Rüschendorf Germany
Eero Lehtonen Finland
Corrinne G. Lobe Canada
Gabriele Richard United States
Hélène Baribault United States
John J. Wysolmerski United States
Mustafa Tekin United States
Kenro Kusumi United States
Gudrun Nürnberg Germany
Andrew Read United Kingdom
Charlene J. Williams relative to Franz Rüschendorf Germany Franz Rüschendorf's profile →
Citations per field
00.5×4.6×
Franz Rüschendorf · 1×
Citations per year

Countries citing papers authored by Charlene J. Williams

Since Specialization
Citations

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

Fields of papers citing papers by Charlene J. Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 201820
2 200631
3 200620
4 200535
5 2004293
6 200354
7 200285
8 2002161
9
Inferences on the phylogenetic relationships of Succineidae (Mollusca, Pulmonata) based on 18S rRNA gene
20017
10 199913
11 199721
12 199611
13 199669
14 199659
15 199559
16 199550
17 199381
18 199229
19 19906
20
Prognostically significant protein components of human breast cancer tissues.
197610

About Charlene J. Williams

Charlene J. Williams is a scholar working on Immunology and Allergy, Rheumatology and Nephrology, having authored 64 papers that have together received 3.2k indexed citations. Recurring topics across this work include Osteoarthritis Treatment and Mechanisms (17 papers), Cell Adhesion Molecules Research (13 papers), Connective tissue disorders research (12 papers), Alkaline Phosphatase Research Studies (10 papers), Gout, Hyperuricemia, Uric Acid (7 papers), Bone Metabolism and Diseases (6 papers), Dermatological and Skeletal Disorders (5 papers) and Monoclonal and Polyclonal Antibodies Research (5 papers). The work is most often cited by research in Rheumatology (760 citations), Immunology and Allergy (294 citations) and Endocrine and Autonomic Systems (279 citations). Charlene J. Williams has collaborated with scholars based in United States, United Kingdom and Chile. Frequent co-authors include Steven L. Sabol, Kenichi Yoshikawa, Darwin J. Prockop, Eileen L. Considine, Francesco Ramirez, Mon‐Li Chu, F. José, Robert V. Considine, Antonio J. Reginato and Thomas M. Hyde. Their work appears in journals such as Nature, Journal of Biological Chemistry and The EMBO Journal.

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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