Brian Topp

1.2k citations
21 papers · 874 · h-index 11

Impact in

Papers in

    • Cancer Immunotherapy and Biomarkers 10
    • CAR-T cell therapy research 3
    • Metabolism, Diabetes, and Cancer 4

Brian Topp

20 papers receiving 833 citations

Peers

Brian Topp
Comparison fields: 5 of 88
  • Endocrinology, Diabetes and Metabolism 380
  • Surgery 407
  • Genetics 212
  • Modeling and Simulation 33
  • Molecular Biology 362
Replace Eliana Polisecki with:
Eliana Polisecki United States
Parag Garhyan United States
Teun M. Post Netherlands
Michiel Adriaens Netherlands
Steen H. Ingwersen Denmark
Marlena Maziarz United States
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Dragi Anevski Sweden
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Kashyap Patel United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Brian Topp

Since Specialization
Citations

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

Fields of papers citing papers by Brian Topp

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001312
2 2000214
3 201864
4 201960
5 200455
6 200747
7 200120
8 202319
9 202119
10 200914
11 202113
12 20248
13 20237
14 20216
15 20235
16 20213
17 20243
18 20192
19 20231
20 20201

About Brian Topp

Brian Topp is a scholar working on Oncology, Molecular Biology, Surgery, Genetics and Computational Theory and Mathematics, having authored 21 papers that have together received 874 indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (10 papers), Pancreatic function and diabetes (6 papers), Metabolism, Diabetes, and Cancer (4 papers), Diabetes and associated disorders (4 papers), Computational Drug Discovery Methods (3 papers), CAR-T cell therapy research (3 papers), Cancer Genomics and Diagnostics (3 papers) and Mathematical Biology Tumor Growth (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (380 citations), Surgery (407 citations), Genetics (212 citations), Modeling and Simulation (33 citations) and Molecular Biology (362 citations). Brian Topp has collaborated with scholars based in United States, Canada and Spain. Frequent co-authors include Diane T. Finegood, M. Dawn McArthur, Robin E. Buckingham, Thomas B. Leonard, Keith Promislow, Robert M. Miura, Laura L. Atkinson, Alexandra Snyder, Marjoleen Nijsen and Jason R. Chan. Their work appears in journals such as CPT Pharmacometrics & Systems Pharmacology, Cancer Cell, British Journal of Cancer, Journal of Diabetes Science and Technology and Diabetes.

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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