Kathryn M. Appleton

543 citations
14 papers · 410 · h-index 11

Impact in

Papers in

Kathryn M. Appleton

14 papers receiving 409 citations

Peers

Kathryn M. Appleton
Comparison fields: 5 of 62
  • Cellular and Molecular Neuroscience 139
  • Molecular Biology 309
  • Oncology 58
  • Computational Theory and Mathematics 37
  • Cell Biology 35
Replace Yubo Cao with:
Yubo Cao China
Étienne Khoury Canada
Shu Z. Wiley United States
Stephen W. Young United States
Tabetha M. Bonacci United States
Charu Gupta United States
Yingli Ma United States
Justine S. Paradis Canada
Ryoji Kise Japan
Lama Yamani Canada
Kathryn M. Appleton relative to Yubo Cao China Yubo Cao's profile →
Citations per field
00.5×10.7×
Yubo Cao · 1×
Citations per year

Countries citing papers authored by Kathryn M. Appleton

Since Specialization
Citations

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

Fields of papers citing papers by Kathryn M. Appleton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kathryn M. Appleton. 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 Kathryn M. Appleton. The network helps show where Kathryn M. Appleton may publish in the future.

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 2016160
2 201343
3 201638
4 201630
5 200930
6 202121
7 201321
8 201417
9 201417
10 201312
11 201310
12 20219
13 20191
14 20211

About Kathryn M. Appleton

Kathryn M. Appleton is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Oncology, Physiology and Genetics, having authored 14 papers that have together received 410 indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (7 papers), Neuropeptides and Animal Physiology (5 papers), Protein Kinase Regulation and GTPase Signaling (4 papers), Melanoma and MAPK Pathways (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), PI3K/AKT/mTOR signaling in cancer (2 papers), CAR-T cell therapy research (2 papers) and PARP inhibition in cancer therapy (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (139 citations), Molecular Biology (309 citations), Oncology (58 citations), Computational Theory and Mathematics (37 citations) and Cell Biology (35 citations). Kathryn M. Appleton has collaborated with scholars based in United States, Puerto Rico and Lebanon. Frequent co-authors include Louis M. Luttrell, Yuri K. Peterson, Mi‐Hye Lee, Thomas A. Morinelli, Stéphane A. Laporte, Erik G. Strungs, Hesham M. El‐Shewy, Thomas A. Morinelli, Parker C. Wilson and Ayad A. Jaffa. Their work appears in journals such as Journal of Lipid Research, Cancers, Journal of Biological Chemistry, Nature and Methods in enzymology on CD-ROM/Methods in enzymology.

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.

Explore authors with similar magnitude of impact