Joel Cassel

2.3k citations
70 papers · 1.4k · h-index 22

Impact in

Papers in

Joel Cassel

63 papers receiving 1.3k citations

Peers

Joel Cassel
Comparison fields: 5 of 97
  • Cellular and Molecular Neuroscience 340
  • Molecular Biology 741
  • Neurology 146
  • Genetics 73
  • Pharmacology 108
Replace James Ziogas with:
James Ziogas Australia
Mark Namchuk United States
Lisa M. Johnson United States
Eva-Anne Subileau Austria
Yumi Yamamoto Netherlands
David J. Morgans United States
Laura Gaeta Italy
Claude Dagenais Canada
Jinling Hou United States
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Citations per field
00.5×7.3×
James Ziogas · 1×
Citations per year

Countries citing papers authored by Joel Cassel

Since Specialization
Citations

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

Fields of papers citing papers by Joel Cassel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999130
2 201992
3 200278
4 202172
5 202167
6 201564
7 200562
8 202359
9 201958
10 201354
11 199846
12 202329
13 200026
14 201225
15 201024
16 202124
17 201224
18 200724
19 200323
20 200323

About Joel Cassel

Joel Cassel is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Pharmacology, Computational Theory and Mathematics and Infectious Diseases, having authored 70 papers that have together received 1.4k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (20 papers), Receptor Mechanisms and Signaling (19 papers), Pharmacological Receptor Mechanisms and Effects (14 papers), Computational Drug Discovery Methods (7 papers), Amyotrophic Lateral Sclerosis Research (5 papers), Cannabis and Cannabinoid Research (5 papers), Protein Degradation and Inhibitors (5 papers) and Pain Mechanisms and Treatments (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (340 citations), Molecular Biology (741 citations), Neurology (146 citations), Genetics (73 citations) and Pharmacology (108 citations). Joel Cassel has collaborated with scholars based in United States, Cameroon and Germany. Frequent co-authors include Robert N. DeHaven, Allen B. Reitz, Jeffrey D. Daubert, Diane L. DeHaven‐Hudkins, Erik Mansson, Tony L. Yaksh, Joseph M. Salvino, Roland E. Dolle, Murray Goodman and Mark E. McDonnell. Their work appears in journals such as Bioorganic & Medicinal Chemistry Letters, Cancer Research, Journal of Medicinal Chemistry, Journal of Natural Products and Cell Reports.

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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