D End

1.2k citations
19 papers · 1.1k · h-index 15

Impact in

Papers in

D End

19 papers receiving 1.0k citations

Peers

D End
Comparison fields: 5 of 83
  • Oncology 280
  • Cellular and Molecular Neuroscience 176
  • Cancer Research 129
  • Molecular Biology 607
  • Genetics 76
Replace Kenneth J. Shaw with:
Kenneth J. Shaw United States
Elizabeth Keech United Kingdom
Hong Chang United States
Karl Maly Austria
David W. End United States
Ute Lehmann Germany
Shonna A. Moodie United States
Roland Neuhaus Germany
Kelli Glenn United States
Christina Nielsen Denmark
D End relative to Kenneth J. Shaw United States Kenneth J. Shaw's profile →
Citations per field
00.5×1.5×
Kenneth J. Shaw · 1×
Citations per year

Countries citing papers authored by D End

Since Specialization
Citations

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

Fields of papers citing papers by D End

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 1981244
2 2000234
3 2004115
4 200281
5
Preclinical antitumor activity and pharmacodynamic studies with the farnesyl protein transferase inhibitor R115777 in human breast cancer.
200180
6
The farnesyltransferase inhibitor R115777 reduces hypoxia and matrix metalloproteinase 2 expression in human glioma xenograft.
200363
7 198354
8 199242
9 198224
10 200522
11 197722
12 200820
13 200519
14 198119
15 198017
16 19859
17 20065
18
Characterization of a high affinity interleukin-1 (IL-1) specific binding site in a human synovial sarcoma (Hs431) cell line.
19903
19 19792

About D End

D End is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Oncology, Cell Biology and Organic Chemistry, having authored 19 papers that have together received 1.1k indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (4 papers), Neuroscience and Neuropharmacology Research (3 papers), Ubiquitin and proteasome pathways (2 papers), Endoplasmic Reticulum Stress and Disease (2 papers), Protein Kinase Regulation and GTPase Signaling (2 papers), Platelet Disorders and Treatments (2 papers), Nerve injury and regeneration (2 papers) and Polyamine Metabolism and Applications (2 papers). The work is most often cited by research in Oncology (280 citations), Cellular and Molecular Neuroscience (176 citations), Cancer Research (129 citations), Molecular Biology (607 citations) and Genetics (76 citations). D End has collaborated with scholars based in United States, Cameroon and Belgium. Frequent co-authors include Gordon Guroff, Karen Huff, Elizabeth Cohen–Jonathan, Caroline Delmas, Christine Toulas, Gilles Favre, Seiichi Hashimoto, N. Tolson, Patrick Angibaud and Marc Venet. Their work appears in journals such as Journal of Biological Chemistry, Bioorganic & Medicinal Chemistry Letters, Blood, Biochimica et Biophysica Acta (BBA) - General Subjects and Journal of Toxicology and Environmental Health.

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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