John P. Mathis

803 citations
17 papers · 695 · h-index 12

Impact in

Papers in

    • Neuropeptides and Animal Physiology 16
    • Neuroscience and Neuropharmacology Research 2
    • Receptor Mechanisms and Signaling 15
    • Chemical Synthesis and Analysis 3
    • Pharmacological Receptor Mechanisms and Effects 2

John P. Mathis

17 papers receiving 678 citations

Peers

John P. Mathis
Comparison fields: 5 of 57
  • Cellular and Molecular Neuroscience 553
  • Endocrine and Autonomic Systems 70
  • Reproductive Medicine 83
  • Physiology 234
  • Molecular Biology 445
Replace Kazuhisa Kashimoto with:
Kazuhisa Kashimoto Japan
S. Zakarian United Kingdom
J.A. Biggins United Kingdom
D. Gully France
C. Ventra Italy
H Bonin Canada
S P Wilson United States
Jean F. Schaefer United States
Jean Danao United States
Aline Brouard France
John P. Mathis relative to Kazuhisa Kashimoto Japan Kazuhisa Kashimoto's profile →
Citations per field
00.5×1.5×2.4×
Kazuhisa Kashimoto · 1×
Citations per year

Countries citing papers authored by John P. Mathis

Since Specialization
Citations

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

Fields of papers citing papers by John P. Mathis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John P. Mathis. 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 John P. Mathis. The network helps show where John P. Mathis may publish in the future.

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 1998166
2 1993132
3 1997107
4 199847
5 200043
6 199637
7 199237
8 200020
9 199919
10 199818
11 199216
12 199612
13 199610
14 200110
15 200110
16 20088
17 20003

About John P. Mathis

John P. Mathis is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Physiology, Reproductive Medicine and Surgery, having authored 17 papers that have together received 695 indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (16 papers), Receptor Mechanisms and Signaling (15 papers), Hypothalamic control of reproductive hormones (3 papers), Pain Mechanisms and Treatments (3 papers), Chemical Synthesis and Analysis (3 papers), Pharmacological Receptor Mechanisms and Effects (2 papers), Cardiovascular, Neuropeptides, and Oxidative Stress Research (2 papers) and Neuroscience and Neuropharmacology Research (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (553 citations), Endocrine and Autonomic Systems (70 citations), Reproductive Medicine (83 citations), Physiology (234 citations) and Molecular Biology (445 citations). John P. Mathis has collaborated with scholars based in United States. Frequent co-authors include Gavril W. Pasternak, Iris Lindberg, Grace C. Rossi, Jennifer P. Ryan‐Moro, Sharon R. Letchworth, Liza Leventhal, Claude Lazure, Mary B. Breslin, Nabil G. Seidah and Suzanne Benjannet. Their work appears in journals such as The Journal of Comparative Neurology, Journal of Biological Chemistry, Endocrinology, Brain Research and Journal of Neurochemistry.

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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