Frank Feleppa

2.1k total citations · 1 hit paper
9 papers, 1.5k citations indexed

About

Frank Feleppa is a scholar working on Oncology, Molecular Biology and Genetics. According to data from OpenAlex, Frank Feleppa has authored 9 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Oncology, 4 papers in Molecular Biology and 3 papers in Genetics. Recurrent topics in Frank Feleppa's work include Peptidase Inhibition and Analysis (2 papers), HER2/EGFR in Cancer Research (2 papers) and Cell death mechanisms and regulation (1 paper). Frank Feleppa is often cited by papers focused on Peptidase Inhibition and Analysis (2 papers), HER2/EGFR in Cancer Research (2 papers) and Cell death mechanisms and regulation (1 paper). Frank Feleppa collaborates with scholars based in Australia, Italy and Belgium. Frank Feleppa's co-authors include Stephen B. Fox, Elgene Lim, Teresa Ward, Geoffrey J. Lindeman, Gordon K. Smyth, François Vaillant, Jane E. Visvader, David Gyorki, Max Yan and Heather Thorne and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Medicine and Journal of Clinical Oncology.

In The Last Decade

Frank Feleppa

9 papers receiving 1.5k citations

Hit Papers

Aberrant luminal progenitors as the candidate target popu... 2009 2026 2014 2020 2009 250 500 750 1000

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Frank Feleppa Australia 8 963 816 513 238 145 9 1.5k
Frédérique Spyratos France 24 660 0.7× 878 1.1× 788 1.5× 280 1.2× 204 1.4× 41 1.7k
Keltouma Driouch France 24 687 0.7× 1.3k 1.6× 425 0.8× 335 1.4× 264 1.8× 41 1.8k
Yongping Crawford United States 14 581 0.6× 1.1k 1.3× 450 0.9× 141 0.6× 133 0.9× 16 1.5k
Teresa Ward New Zealand 13 974 1.0× 1.2k 1.5× 503 1.0× 308 1.3× 258 1.8× 15 1.8k
Annie S.Y. Chan China 19 581 0.6× 1.1k 1.3× 465 0.9× 184 0.8× 168 1.2× 20 1.8k
Stephan Duss Switzerland 12 682 0.7× 669 0.8× 520 1.0× 226 0.9× 196 1.4× 13 1.3k
Sergio Aguggini Italy 17 665 0.7× 470 0.6× 709 1.4× 159 0.7× 141 1.0× 34 1.3k
Sana Yokoi Japan 21 498 0.5× 870 1.1× 297 0.6× 150 0.6× 378 2.6× 43 1.4k
J. S. Reis-Filho United Kingdom 14 1.0k 1.0× 812 1.0× 884 1.7× 314 1.3× 309 2.1× 24 2.0k
Giovanni Allevi Italy 17 603 0.6× 437 0.5× 669 1.3× 150 0.6× 136 0.9× 36 1.2k

Countries citing papers authored by Frank Feleppa

Since Specialization
Citations

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

Fields of papers citing papers by Frank Feleppa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frank Feleppa

This figure shows the co-authorship network connecting the top 25 collaborators of Frank Feleppa. A scholar is included among the top collaborators of Frank Feleppa based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Frank Feleppa. Frank Feleppa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Agarwal, Rishu, Stephen Lade, Danny Liew, et al.. (2015). Role of immunohistochemistry in the era of genetic testing in MYC -positive aggressive B-cell lymphomas: a study of 209 cases. Journal of Clinical Pathology. 69(3). 266–270. 28 indexed citations
2.
Liubinas, Simon V., Giovanna M. D’Abaco, Bradford A. Moffat, et al.. (2014). IDH1 mutation is associated with seizures and protoplasmic subtype in patients with low‐grade gliomas. Epilepsia. 55(9). 1438–1443. 58 indexed citations
3.
Oakes, Samantha R., François Vaillant, Elgene Lim, et al.. (2011). Sensitization of BCL-2–expressing breast tumors to chemotherapy by the BH3 mimetic ABT-737. Proceedings of the National Academy of Sciences. 109(8). 2766–2771. 150 indexed citations
4.
Lim, Elgene, François Vaillant, Di Wu, et al.. (2009). Aberrant luminal progenitors as the candidate target population for basal tumor development in BRCA1 mutation carriers. Nature Medicine. 15(8). 907–913. 1048 indexed citations breakdown →
5.
Ng, Ashley P., et al.. (2006). The sensitivity of CD138 immunostaining of bone marrow trephine specimens for quantifying marrow involvement in MGUS and myeloma, including samples with a low percentage of plasma cells.. PubMed. 91(7). 972–5. 39 indexed citations
6.
Mann, G. Bruce, et al.. (2005). Reliance on Hormone Receptor Assays of Surgical Specimens May Compromise Outcome in Patients With Breast Cancer. Journal of Clinical Oncology. 23(22). 5148–5154. 113 indexed citations
8.
Busmanis, Inny, Frank Feleppa, Katherine McGrath, et al.. (1994). Analysis of cerbB2 expression using a panel of 6 commercially available antibodies. Pathology. 26(3). 261–267. 44 indexed citations
9.
Feleppa, Frank, et al.. (1986). Development of Monoclonal Antibodies to the Human Breast Carcinoma Cell Line PMC42<xref ref-type="fn" rid="FN1">2</xref>. JNCI Journal of the National Cancer Institute. 77(1). 1–15. 16 indexed citations

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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