Megan M. Davis

88 total papers · 7.8k total citations
28 papers, 1.1k citations indexed

About

Megan M. Davis is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Megan M. Davis has authored 28 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Oncology, 13 papers in Molecular Biology and 8 papers in Immunology. Recurrent topics in Megan M. Davis's work include CAR-T cell therapy research (23 papers), Viral Infectious Diseases and Gene Expression in Insects (7 papers) and CRISPR and Genetic Engineering (5 papers). Megan M. Davis is often cited by papers focused on CAR-T cell therapy research (23 papers), Viral Infectious Diseases and Gene Expression in Insects (7 papers) and CRISPR and Genetic Engineering (5 papers). Megan M. Davis collaborates with scholars based in United States, Czechia and China. Megan M. Davis's co-authors include Joseph A. Fraietta, J. Joseph Melenhorst, Carl H. June, Bruce L. Levine, Simon F. Lacey, Michael C. Milone, Albert W. Probert, Gerald P. Schielke, Kevin Wang and Xiaodong Ren and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and Blood.

In The Last Decade

Megan M. Davis

28 papers receiving 1.0k citations

Hit Papers

Deletion of the inhibitor... 2023 2026 2024 2023 25 50 75

Author Peers

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

Author Last Decade Papers Cites
Megan M. Davis 780 489 284 229 218 28 1.1k
John T. Kemshead 438 0.6× 463 0.9× 225 0.8× 130 0.6× 176 0.8× 35 1.2k
Christopher D. Chien 694 0.9× 446 0.9× 301 1.1× 170 0.7× 248 1.1× 32 1.1k
Qian Zhang 591 0.8× 296 0.6× 252 0.9× 112 0.5× 118 0.5× 30 872
Ryan Cross 803 1.0× 406 0.8× 434 1.5× 286 1.2× 173 0.8× 30 1.2k
Tatsuki Ueda 520 0.7× 641 1.3× 279 1.0× 142 0.6× 135 0.6× 24 1.0k
Martín Bonamino 330 0.4× 663 1.4× 193 0.7× 89 0.4× 208 1.0× 47 1.1k
Victoria Casado‐Medrano 740 0.9× 462 0.9× 385 1.4× 260 1.1× 201 0.9× 22 1.1k
Ana Kostić 477 0.6× 282 0.6× 109 0.4× 182 0.8× 76 0.3× 39 980
Chuang Sun 844 1.1× 385 0.8× 385 1.4× 325 1.4× 231 1.1× 18 1.1k
Scott H. Olejniczak 431 0.6× 516 1.1× 283 1.0× 60 0.3× 64 0.3× 41 1.2k

Countries citing papers authored by Megan M. Davis

Since Specialization
Citations

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

Fields of papers citing papers by Megan M. Davis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Megan M. Davis. 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 Megan M. Davis. The network helps show where Megan M. Davis may publish in the future.

Co-authorship network of co-authors of Megan M. Davis

This figure shows the co-authorship network connecting the top 25 collaborators of Megan M. Davis. A scholar is included among the top collaborators of Megan M. Davis 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 Megan M. Davis. Megan M. Davis 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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