Ken Wasserman

2.8k citations
22 papers · 2.4k indexed · 1 hit paper · h-index 14
Topics
Immune Cell Function and Interaction (10 papers)Immunotherapy and Immune Responses (6 papers)Cell Adhesion Molecules Research (6 papers)
Partner nations
United StatesSwedenItaly

In The Last Decade

Ken Wasserman

21 papers receiving 2.3k citations

Hit Papers

Human endothelial cells express CCR2 and respond to MCP-1...20002026200820172000200400600

Peers

Ken Wasserman
Comparison fields: 5 of 94
  • Immunology 1.2k
  • Oncology 1.1k
  • Molecular Biology 786
  • Immunology and Allergy 307
  • Cancer Research 231
Replace Roy A. Fava with:
Roy A. Fava United States
M. Asif Amin United States
Mizuko Mamura Japan
Yuuichi Hirata Japan
T Matsuda Japan
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R E Gay Switzerland
Ken Wasserman relative to Roy A. Fava United States Roy A. Fava's profile →
Citations per field
00.5×1.5×
Roy A. Fava · 1×
Citations per year

Countries citing papers authored by Ken Wasserman

Since Specialization
Citations

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

Fields of papers citing papers by Ken Wasserman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ken Wasserman

This figure shows the co-authorship network connecting the top 25 collaborators of Ken Wasserman. A scholar is included among the top collaborators of Ken Wasserman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ken Wasserman. Ken Wasserman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 0
3 154
4 8
5 217
6
Human endothelial cells express CCR2 and respond to MCP-1: direct role of MCP-1 in angiogenesis and tumor progressionbreakdown →
719
7 194
8 441
9 2
10 27
11 16
12 3
13 13
14 301
15 40
16
Zymographic analysis of extracellular, released and cell-associated proteases of rat interleukin 2-activated natural killer (A-NK) cells.
3
17 11
18 16
19 112
20
A subpopulation of allospecific cytotoxic T-cell precursors with phenotypic characteristics of natural killer cells.
1

About Ken Wasserman

Ken Wasserman is a scholar working on Immunology and Allergy, Immunology and Oncology, having authored 22 papers that have together received 2.4k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (10 papers), Immunotherapy and Immune Responses (6 papers) and Cell Adhesion Molecules Research (6 papers). The work is most often cited by research in Immunology (1.2k citations), Immunology and Allergy (307 citations) and Oncology (1.1k citations). Ken Wasserman has collaborated with scholars based in United States, Sweden and Italy. Frequent co-authors include Rosalba Salcedo, Joost J. Oppenheim, Howard A. Young, William J. Murphy, Hynda K. Kleinman, Jerrold M. Ward, M. Lourdes Ponce, Rolf Kiessling, Koji Kono and Max Petersson. Their work appears in journals such as The Journal of Experimental Medicine, Blood and The Journal of Immunology.

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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