Marie Prewett

77 total papers · 3.7k total citations
34 papers, 2.9k citations indexed

About

Marie Prewett is a scholar working on Oncology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Marie Prewett has authored 34 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Oncology, 17 papers in Molecular Biology and 14 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Marie Prewett's work include Monoclonal and Polyclonal Antibodies Research (13 papers), HER2/EGFR in Cancer Research (11 papers) and Cancer Treatment and Pharmacology (8 papers). Marie Prewett is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (13 papers), HER2/EGFR in Cancer Research (11 papers) and Cancer Treatment and Pharmacology (8 papers). Marie Prewett collaborates with scholars based in United States, France and Japan. Marie Prewett's co-authors include Neil I. Goldstein, Patricia Rockwell, John Mendelsohn, Andrea T. Hooper, Daniel J. Hicklin, Harlan W. Waksal, Rajiv Bassi, Peter Böhlen, Lee M. Ellis and Yiwen Li and has published in prestigious journals such as Journal of Biological Chemistry, Cancer and Cancer Research.

In The Last Decade

Marie Prewett

33 papers receiving 2.8k citations

Hit Papers

Biological efficacy of a ... 1995 2026 2005 2015 1995 1999 200 400 600

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Marie Prewett 1.7k 1.4k 816 665 510 34 2.9k
Vincenzo Damiano 1.9k 1.1× 1.4k 1.0× 1.2k 1.4× 339 0.5× 460 0.9× 62 3.2k
Paul Kussie 1.1k 0.6× 2.1k 1.5× 420 0.5× 693 1.0× 442 0.9× 47 3.5k
Dana D. Hu‐Lowe 1.0k 0.6× 1.8k 1.2× 798 1.0× 340 0.5× 778 1.5× 33 3.0k
Jane Kendrew 1.1k 0.7× 1.5k 1.1× 638 0.8× 312 0.5× 561 1.1× 33 2.7k
Eric A. Armstrong 1.7k 1.0× 1.3k 0.9× 1.1k 1.4× 436 0.7× 401 0.8× 51 3.0k
David R. Shalinsky 1.7k 1.0× 2.3k 1.6× 1.0k 1.2× 294 0.4× 1.3k 2.5× 52 4.3k
Cammie Rinehart 1.7k 1.0× 1.7k 1.2× 568 0.7× 719 1.1× 327 0.6× 19 2.8k
Kenneth K. Iwata 1.8k 1.1× 1.9k 1.4× 971 1.2× 188 0.3× 520 1.0× 49 3.4k
Tomoyuki Kawamoto 1.7k 1.0× 1.5k 1.1× 567 0.7× 1.0k 1.5× 269 0.5× 26 3.0k
Pamela A. Trail 1.5k 0.9× 1.7k 1.2× 330 0.4× 1.2k 1.8× 521 1.0× 61 3.6k

Countries citing papers authored by Marie Prewett

Since Specialization
Citations

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

Fields of papers citing papers by Marie Prewett

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marie Prewett

This figure shows the co-authorship network connecting the top 25 collaborators of Marie Prewett. A scholar is included among the top collaborators of Marie Prewett 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 Marie Prewett. Marie Prewett is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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