Peter Mullen

82 papers receiving 3.4k citations

Peter Mullen's Hit Papers

The interplay between cell signalling and the mevalonate pathway in cancer 2016 · 513 citations
5130+3+6Years since publication100200300400500

Peers

Peter Mullen
Comparison fields: 5 of 134
  • Cancer Research 1.0k
  • Oncology 682
  • Molecular Biology 1.7k
  • Reproductive Medicine 134
  • Cell Biology 229
Replace Tim H.‐M. Huang with:
Tim H.‐M. Huang United States
Stewart G. Martin United Kingdom
Juliane M. Jürgensmeier United States
J. Chuck Harrell United States
Joy C. Yang United States
Gong Yang China
Annamaria Biroccio Italy
Markus Christmann Germany
Eugenio Erba Italy
Dimitris Athineos United Kingdom
Peter Mullen relative to Tim H.‐M. Huang United States Tim H.‐M. Huang's profile →
Citations per field
00.5×1.5×
Tim H.‐M. Huang · 1×
Citations per year

Countries citing papers authored by Peter Mullen

Since Specialization
Citations

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

Fields of papers citing papers by Peter Mullen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The interplay between cell signalling and the mevalonate pathway in cancer
Hit paper breakdown →
2016513
2 2018203
3 2012163
4 2010142
5 2009139
6 2005128
7 202197
8 199791
9 201575
10 201472
11 200968
12 201466
13 200765
14 201964
15 201164
16 200163
17 201258
18 201354
19 201753
20 199653

About Peter Mullen

Peter Mullen is a scholar working on Molecular Biology, Oncology, Cancer Research, Pulmonary and Respiratory Medicine and Surgery, having authored 85 papers that have together received 3.5k indexed citations. Recurring topics across this work include HER2/EGFR in Cancer Research (9 papers), Cancer Genomics and Diagnostics (8 papers), Estrogen and related hormone effects (8 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), Cancer, Lipids, and Metabolism (7 papers), Cell Adhesion Molecules Research (6 papers), Lipoproteins and Cardiovascular Health (5 papers) and Renal cell carcinoma treatment (5 papers). The work is most often cited by research in Cancer Research (1.0k citations), Oncology (682 citations), Molecular Biology (1.7k citations), Reproductive Medicine (134 citations) and Cell Biology (229 citations). Peter Mullen has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Simon P. Langdon, Linda Z. Penn, David J. Harrison, Rosemary Yu, Joseph Longo, Michael C. Archer, Dana Faratian, Carol Ward, William R. Miller and John F. Smyth. Their work appears in journals such as Cancer Research, British Journal of Cancer, Oncotarget, Clinical Cancer Research and The Journal of Steroid Biochemistry and Molecular Biology.

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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