David A. Moore

12.5k citations
30 papers · 737 · h-index 16

Impact in

    • Cancer Genomics and Diagnostics
  • Oncology top 10%
    • Cancer Cells and Metastasis
    • Cancer Immunotherapy and Biomarkers
    • Cutaneous Melanoma Detection and Management

Papers in

David A. Moore

27 papers receiving 725 citations

Peers

David A. Moore
Comparison fields: 5 of 87
  • Cancer Research 190
  • Oncology 337
  • Reproductive Medicine 93
  • Obstetrics and Gynecology 60
  • Biotechnology 58
Replace Takafumi Koyama with:
Takafumi Koyama Japan
Tinghui Wu Taiwan
Elena Poddubskaya Russia
Natalie Y.L. Ngoi Singapore
Keisuke Tamari Japan
Marlies S. Reimers Netherlands
Andrew P. Sciallis United States
Sebastian Szubert Poland
Shane R. Stecklein United States
David A. Moore relative to Takafumi Koyama Japan Takafumi Koyama's profile →
Citations per field
00.5×10×13.5×
Takafumi Koyama · 1×
Citations per year

Countries citing papers authored by David A. Moore

Since Specialization
Citations

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

Fields of papers citing papers by David A. Moore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David A. Moore. 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 David A. Moore. The network helps show where David A. Moore may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Heterogeneity of erbB-2 gene amplification in bladder cancer.
1993161
2 201768
3 201867
4 201866
5 199858
6 199541
7 201740
8 199631
9 202424
10 201824
11 202322
12 201522
13 201719
14 201719
15 202415
16 201515
17 201811
18 20138
19 20118
20 20235

About David A. Moore

David A. Moore is a scholar working on Cancer Research, Molecular Biology, Pulmonary and Respiratory Medicine, Oncology and Pathology and Forensic Medicine, having authored 30 papers that have together received 737 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (11 papers), Cutaneous Melanoma Detection and Management (4 papers), Lung Cancer Treatments and Mutations (4 papers), Molecular Biology Techniques and Applications (3 papers), Cell Image Analysis Techniques (2 papers), Melanoma and MAPK Pathways (2 papers), Endometrial and Cervical Cancer Treatments (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Cancer Research (190 citations), Oncology (337 citations), Reproductive Medicine (93 citations), Obstetrics and Gynecology (60 citations) and Biotechnology (58 citations). David A. Moore has collaborated with scholars based in United Kingdom, United States and Sweden. Frequent co-authors include Fred Waldman, F Gudat, Guido Sauter, Michael J. Mihatsch, Patrick Carroll, Russell Kerschmann, Holger Moch, Karen Chew, John Le Quesne and Gregory P. Sutton. Their work appears in journals such as Nature Communications, Gynecologic Oncology, Journal of Clinical Pathology, Oncotarget and Journal of Molecular Diagnostics.

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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