Patrick Williamson

76 papers receiving 4.0k citations

Peers

Patrick Williamson
Comparison fields: 5 of 158
  • Immunology 1.1k
  • Hematology 467
  • Physiology 982
  • Molecular Biology 2.2k
  • Genetics 310
Replace Motowo Tomita with:
Motowo Tomita Japan
Frank S. Lee United States
Marshall A. Lichtman United States
Gray D. Shaw United States
Shin‐ichi Ishii Japan
Gerrit Koopman Netherlands
Janice Y. Chou United States
Stuart Rudikoff United States
John C. Speck United States
Paul H. Weinreb United States
Patrick Williamson relative to Motowo Tomita Japan Motowo Tomita's profile →
Citations per field
00.5×1.5×1.8×
Motowo Tomita · 1×
Citations per year

Countries citing papers authored by Patrick Williamson

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Williamson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 201918
2 201228
3 201215
4 20115
5 2009112
6 2004106
7 200120
8 200037
9 199927
10 1999114
11 1999107
12 199850
13 1994107
14 19928
15 199214
16 19915
17 1991162
18 19915
19 198916
20 1982141

About Patrick Williamson

Patrick Williamson is a scholar working on Forestry, Physiology, Immunology, Agronomy and Crop Science and Hematology, having authored 77 papers that have together received 4.2k indexed citations. Recurring topics across this work include Lipid Membrane Structure and Behavior (30 papers), Erythrocyte Function and Pathophysiology (25 papers), Phagocytosis and Immune Regulation (14 papers), Ruminant Nutrition and Digestive Physiology (8 papers), Cell death mechanisms and regulation (7 papers), Drug Transport and Resistance Mechanisms (7 papers), RNA Interference and Gene Delivery (6 papers) and Genetic and phenotypic traits in livestock (6 papers). The work is most often cited by research in Immunology (1.1k citations), Hematology (467 citations), Physiology (982 citations), Molecular Biology (2.2k citations) and Genetics (310 citations). Patrick Williamson has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Robert Schlegel, Margaret S. Halleck, Stephen Krahling, Xiaojing Tang, Melissa K. Callahan, Joost C. M. Holthuis, Hyeryun Choe, Paul Comfurius, Edouard M. Bevers and R.F.A. Zwaal. Their work appears in journals such as Journal of Cellular Physiology, Biochemistry, The Journal of Agricultural Science, Journal of Biological Chemistry and Cell Death and Differentiation.

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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