Jennifer M. Shipman

1.2k citations
13 papers · 539 indexed · h-index 11
Topics
PI3K/AKT/mTOR signaling in cancer (3 papers)Protein Kinase Regulation and GTPase Signaling (2 papers)Peptidase Inhibition and Analysis (2 papers)
Partner nations
United StatesCanadaJapan

In The Last Decade

Jennifer M. Shipman

13 papers receiving 529 citations

Peers

Jennifer M. Shipman
Comparison fields: 5 of 73
  • Molecular Biology 378
  • Oncology 128
  • Cancer Research 123
  • Pathology and Forensic Medicine 120
  • Organic Chemistry 95
Replace Thomas H. Beckham with:
Thomas H. Beckham United States
Wei Jing China
Wei Wei Prior United States
Linda Rushworth United Kingdom
Paul Tapang United States
Yahao Bu United States
Jun-Ying Zhou United States
Hirokazu Kurokawa Japan
Maı̈na Lepourcelet United States
Naoto Ohi Japan
Jennifer M. Shipman relative to Thomas H. Beckham United States Thomas H. Beckham's profile →
Citations per field
00.5×3.6×
Thomas H. Beckham · 1×
Citations per year

Countries citing papers authored by Jennifer M. Shipman

Since Specialization
Citations

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

Fields of papers citing papers by Jennifer M. Shipman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jennifer M. Shipman

This figure shows the co-authorship network connecting the top 25 collaborators of Jennifer M. Shipman. A scholar is included among the top collaborators of Jennifer M. Shipman 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 Jennifer M. Shipman. Jennifer M. Shipman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
#WorkIndexed citations
1 1
2 4
3 73
4 13
5 30
6 38
7 11
8 46
9 30
10 36
11 22
12 70
13 165

About Jennifer M. Shipman

Jennifer M. Shipman is a scholar working on Toxicology, Oncology and Cancer Research, having authored 13 papers that have together received 539 indexed citations. Recurring topics across this work include PI3K/AKT/mTOR signaling in cancer (3 papers), Protein Kinase Regulation and GTPase Signaling (2 papers) and Peptidase Inhibition and Analysis (2 papers). The work is most often cited by research in Cancer Research (123 citations), Pathology and Forensic Medicine (120 citations) and Molecular Biology (378 citations). Jennifer M. Shipman has collaborated with scholars based in United States, Canada and Japan. Frequent co-authors include Theodore L. DeWeese, William G. Nelson, Nicole Larrier, Richard G. Cutler, Larry E. Dillehay, LaCreis R. Kidd, Hein te Riele, John D. Groopman, Dawn L. Hall and Kevin J. Lumb. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Cancer Research.

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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