Jay B. Fell

3.0k citations
13 papers · 276 · h-index 7

Impact in

    • Synthesis and Catalytic Reactions
    • Catalytic C–H Functionalization Methods
    • Synthesis and biological activity
    • Synthesis and Biological Evaluation
    • Sulfur-Based Synthesis Techniques
    • Asymmetric Synthesis and Catalysis
    • Analytical Chemistry and Chromatography

Papers in

    • Biochemical and Molecular Research 4
    • Protein Kinase Regulation and GTPase Signaling 2
    • Melanoma and MAPK Pathways 2
    • Click Chemistry and Applications 2
    • Carbohydrate Chemistry and Synthesis 2

Jay B. Fell

13 papers receiving 253 citations

Peers

Jay B. Fell
Comparison fields: 5 of 56
  • Organic Chemistry 162
  • Spectroscopy 40
  • Hepatology 18
  • Toxicology 7
  • Molecular Biology 132
Replace Tony Pateman with:
Tony Pateman United Kingdom
Ramesh Kakarla United States
Thomas M. Judge United States
Maxime Soumeillant United States
Patrick Pinto United States
John W. Butcher United States
Dmitry V. Kravchenko Russia
Neil J. Lajkiewicz United States
Pär Nordell Sweden
Jay B. Fell relative to Tony Pateman United Kingdom Tony Pateman's profile →
Citations per field
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Tony Pateman · 1×
Citations per year

Countries citing papers authored by Jay B. Fell

Since Specialization
Citations

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

Fields of papers citing papers by Jay B. Fell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay B. Fell. 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 Jay B. Fell. The network helps show where Jay B. Fell may publish in the future.

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 199661
2 199855
3 200846
4 199830
5 199528
6 200927
7 20197
8 20195
9 19965
10 20205
11 20214
12 20192
13 20241

About Jay B. Fell

Jay B. Fell is a scholar working on Molecular Biology, Organic Chemistry, Oncology, Computational Theory and Mathematics and Hepatology, having authored 13 papers that have together received 276 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (4 papers), Biochemical and Molecular Research (4 papers), Click Chemistry and Applications (2 papers), Protein Kinase Regulation and GTPase Signaling (2 papers), Melanoma and MAPK Pathways (2 papers), HER2/EGFR in Cancer Research (2 papers), Carbohydrate Chemistry and Synthesis (2 papers) and Hepatitis C virus research (2 papers). The work is most often cited by research in Organic Chemistry (162 citations), Spectroscopy (40 citations), Hepatology (18 citations), Toxicology (7 citations) and Molecular Biology (132 citations). Jay B. Fell has collaborated with scholars based in United States. Frequent co-authors include Bing Yan, G. Kumaravel, Gary M. Coppola, James F. Blake, Sonal Rajyaguru, Isabel Nájera, James R. Wareing, Jefferson Chin, R. Hendricks and Steven Swallow. Their work appears in journals such as Bioorganic & Medicinal Chemistry Letters, Journal of Medicinal Chemistry, The Journal of Organic Chemistry, Cancer Research and Molecular Cancer Therapeutics.

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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