Peter C. Brown

38 papers receiving 1.9k citations

Peter C. Brown's Hit Papers

Make It Stick 2014 · 435 citations
4350+4+8Years since publication100200300400

Peers

Peter C. Brown
Comparison fields: 5 of 160
  • Cancer Research 252
  • Family Practice 27
  • Molecular Biology 1.1k
  • Genetics 364
  • Developmental and Educational Psychology 149
Replace Eun‐Kyung Chung with:
Eun‐Kyung Chung South Korea
E. Duvall United Kingdom
Paul M. Heidger United States
Richard März Austria
Antonio Sarikas Germany
Linda Titus United States
Jennifer B. McCormick United States
James Buchanan United Kingdom
Thomas Richter Germany
Debra Rose Wilson United States
Peter C. Brown relative to Eun‐Kyung Chung South Korea Eun‐Kyung Chung's profile →
Citations per field
00.5×10.4×
Eun‐Kyung Chung · 1×
Citations per year

Countries citing papers authored by Peter C. Brown

Since Specialization
Citations

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

Fields of papers citing papers by Peter C. Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Make It Stick
Hit paper breakdown →
2014435
2 1979356
3 1983180
4 1984114
5 1981113
6 1983109
7 198198
8 201493
9 198185
10 198177
11 197968
12 199866
13 198540
14 200739
15 198135
16 201234
17 198432
18 198127
19 197919
20 198718

About Peter C. Brown

Peter C. Brown is a scholar working on Molecular Biology, Public Health, Environmental and Occupational Health, Hematology, Geometry and Topology and Algebra and Number Theory, having authored 40 papers that have together received 2.1k indexed citations. Recurring topics across this work include Acute Lymphoblastic Leukemia research (11 papers), CRISPR and Genetic Engineering (6 papers), Chronic Myeloid Leukemia Treatments (5 papers), Molecular Biology Techniques and Applications (4 papers), Algebraic structures and combinatorial models (3 papers), T-cell and Retrovirus Studies (3 papers), Chromosomal and Genetic Variations (3 papers) and Virus-based gene therapy research (3 papers). The work is most often cited by research in Cancer Research (252 citations), Family Practice (27 citations), Molecular Biology (1.1k citations), Genetics (364 citations) and Developmental and Educational Psychology (149 citations). Peter C. Brown has collaborated with scholars based in United States, Denmark and France. Frequent co-authors include Robert Schimke, Randal J. Kaufman, Henry L. Roediger, Mark A. McDaniel, Thea D. Tlsty, John Papaconstantinou, Stephen M. Beverley, Doris L. Slate, Laura N. Lowes and Michael McGrogan. Their work appears in journals such as Molecular and Cellular Biology, Journal of Biological Chemistry, BMC Bioinformatics, Cold Spring Harbor Symposia on Quantitative Biology and Journal of Natural Products.

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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