Michael E. Hepperle

1.8k citations
31 papers · 1.6k · h-index 19

Impact in

  • Oncology top 5%
    • Cancer Treatment and Pharmacology
    • Cytokine Signaling Pathways and Interactions
    • NF-κB Signaling Pathways

Papers in

    • Cancer Treatment and Pharmacology 16
    • Cytokine Signaling Pathways and Interactions 4
    • Synthetic Organic Chemistry Methods 8

Michael E. Hepperle

31 papers receiving 1.6k citations

Peers

Michael E. Hepperle
Comparison fields: 5 of 85
  • Oncology 726
  • Cancer Research 342
  • Pathology and Forensic Medicine 275
  • Pharmacology 227
  • Organic Chemistry 403
Replace Tisha San Miguel with:
Tisha San Miguel United States
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Citations per field
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Citations per year

Countries citing papers authored by Michael E. Hepperle

Since Specialization
Citations

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

Fields of papers citing papers by Michael E. Hepperle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael E. Hepperle. 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 Michael E. Hepperle. The network helps show where Michael E. Hepperle may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Taxol®: science and applications.
1995321
2
Small molecule inhibitors of IkappaB kinase are selectively toxic for subgroups of diffuse large B-cell lymphoma defined by gene expression profiling.
2005282
3 2005209
4 2006107
5 199877
6 200673
7 200669
8 200643
9 199341
10 199438
11 199637
12 199434
13 200932
14 200227
15 200926
16 199924
17 199723
18 199921
19 199519
20 201019

About Michael E. Hepperle

Michael E. Hepperle is a scholar working on Oncology, Organic Chemistry, Cancer Research, Pharmacology and Cell Biology, having authored 31 papers that have together received 1.6k indexed citations. Recurring topics across this work include Cancer Treatment and Pharmacology (16 papers), Synthetic Organic Chemistry Methods (8 papers), NF-κB Signaling Pathways (5 papers), Melanoma and MAPK Pathways (5 papers), 14-3-3 protein interactions (4 papers), Microtubule and mitosis dynamics (4 papers), Microbial Natural Products and Biosynthesis (4 papers) and Cytokine Signaling Pathways and Interactions (4 papers). The work is most often cited by research in Oncology (726 citations), Cancer Research (342 citations), Pathology and Forensic Medicine (275 citations), Pharmacology (227 citations) and Organic Chemistry (403 citations). Michael E. Hepperle has collaborated with scholars based in United States. Frequent co-authors include Gunda I. Georg, Yajun Xu, Danyi Wen, Yuhua Nong, Louis M. Staudt, Lenny Dang, Richard Eric Davis, Julian Adams, Lloyd T. Lam and Maria Hottelet. Their work appears in journals such as Bioorganic & Medicinal Chemistry Letters, The Journal of Organic Chemistry, Tetrahedron Letters, Journal of Pharmacology and Experimental Therapeutics and Biochemistry.

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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