William K. Chan

36 papers receiving 1.3k citations

Peers

William K. Chan
Comparison fields: 5 of 96
  • Cancer Research 308
  • Aging 37
  • Pharmacology 169
  • Endocrine and Autonomic Systems 116
  • Geriatrics and Gerontology 48
Replace Soona Shin with:
Soona Shin United States
Karl E. Herbert United Kingdom
Marilena Lanzino Italy
Sudhir Chowdhry United Kingdom
Anthony Chan United States
Paolo Moi Italy
Rosemarie Marchan Germany
In Sup Kil South Korea
Lydie Plecitá‐Hlavatá Czechia
Zhimin Yin China
William K. Chan relative to Soona Shin United States Soona Shin's profile →
Citations per field
00.5×3.2×
Soona Shin · 1×
Citations per year

Countries citing papers authored by William K. Chan

Since Specialization
Citations

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

Fields of papers citing papers by William K. Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997424
2 2013147
3 2000118
4 2015107
5 199874
6 201868
7 199965
8 201841
9 200337
10 201035
11 199931
12 201521
13 201421
14 200616
15 201216
16 201913
17 202112
18 201011
19 201411
20 202011

About William K. Chan

William K. Chan is a scholar working on Molecular Biology, Health, Toxicology and Mutagenesis, Cancer Research, Physiology and Pharmacology, having authored 37 papers that have together received 1.4k indexed citations. Recurring topics across this work include Toxic Organic Pollutants Impact (8 papers), Metabolism, Diabetes, and Cancer (5 papers), Adipose Tissue and Metabolism (5 papers), Cancer, Hypoxia, and Metabolism (5 papers), Pharmacogenetics and Drug Metabolism (4 papers), Autophagy in Disease and Therapy (3 papers), Heat shock proteins research (3 papers) and Carcinogens and Genotoxicity Assessment (3 papers). The work is most often cited by research in Cancer Research (308 citations), Aging (37 citations), Pharmacology (169 citations), Endocrine and Autonomic Systems (116 citations) and Geriatrics and Gerontology (48 citations). William K. Chan has collaborated with scholars based in United States, China and Vietnam. Frequent co-authors include Christopher A. Bradfield, John B. Hogenesch, Victoria Jackiw, R. Clark Brown, Gary H. Perdew, Marilyn G. Pray-Grant, Xiaoling Li, Robert Z. Harris, Mamoun M. Alhamadsheh and Vaughn P. Miller. Their work appears in journals such as Biochemical Pharmacology, International Journal of Molecular Sciences, Archives of Biochemistry and Biophysics, Toxicological Sciences and Life Sciences.

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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