Jeffrey D. Kearns

2.3k citations
33 papers · 1.6k indexed · h-index 18

Jeffrey D. Kearns

32 papers receiving 1.6k citations

Peers

Jeffrey D. Kearns
Comparison fields: 5 of 95
  • Cancer Research 818
  • Immunology 920
  • Oncology 506
  • Molecular Biology 725
  • Radiology, Nuclear Medicine and Imaging 143
Replace Shannon L. Werner with:
Shannon L. Werner United States
Guideng Li China
Christos Patriotis United States
John Woronicz United States
Aruna Murti United States
Nathan O. Siemers United States
Guy Werlen United States
Silvia Šurinová United Kingdom
Eiji Kobayashi Japan
Didier Grillot United States
Jeffrey D. Kearns relative to Shannon L. Werner United States Shannon L. Werner's profile →
Citations per field
00.5×3.3×
Shannon L. Werner · 1×
Citations per year

Countries citing papers authored by Jeffrey D. Kearns

Since Specialization
Citations

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

Fields of papers citing papers by Jeffrey D. Kearns

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeffrey D. Kearns. 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 Jeffrey D. Kearns. The network helps show where Jeffrey D. Kearns may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20243
2 20233
3 202216
4 201611
5 201618
6 20161
7 201546
8 201538
9 201335
10 201346
11 2012152
12 201122
13 20110
14 201135
15 200822
16 200856
17 200881
18 2008173
19 2007310
20 2006187

About Jeffrey D. Kearns

Jeffrey D. Kearns is a scholar working on Cancer Research, Oncology and Immunology, having authored 33 papers that have together received 1.6k indexed citations. Recurring topics across this work include NF-κB Signaling Pathways (13 papers), Immune Response and Inflammation (12 papers), Monoclonal and Polyclonal Antibodies Research (9 papers), Cytokine Signaling Pathways and Interactions (9 papers), HER2/EGFR in Cancer Research (6 papers), Lung Cancer Treatments and Mutations (6 papers), Viral Infectious Diseases and Gene Expression in Insects (3 papers) and Colorectal Cancer Treatments and Studies (3 papers). The work is most often cited by research in Cancer Research (818 citations), Immunology (920 citations) and Oncology (506 citations). Jeffrey D. Kearns has collaborated with scholars based in United States, Switzerland and China. Frequent co-authors include Alexander Hoffmann, Shannon L. Werner, Ellen L O'Dea, Soumen Basak, Gourisankar Ghosh, Christine Huang, Hana Kim, Carl F. Ware, Inder M. Verma and Vinay Tergaonkar. Their work appears in journals such as Journal of Clinical Oncology, Molecular Cancer Therapeutics, Immunity, Journal of Biological Chemistry and Journal of Pharmacokinetics and Pharmacodynamics.

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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