Dana Ferraris

124 total papers · 6.1k total citations
68 papers, 4.9k citations indexed

About

Dana Ferraris is a scholar working on Molecular Biology, Oncology and Organic Chemistry. According to data from OpenAlex, Dana Ferraris has authored 68 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 22 papers in Oncology and 16 papers in Organic Chemistry. Recurrent topics in Dana Ferraris's work include PARP inhibition in cancer therapy (14 papers), Amino Acid Enzymes and Metabolism (13 papers) and Chemical Synthesis and Analysis (10 papers). Dana Ferraris is often cited by papers focused on PARP inhibition in cancer therapy (14 papers), Amino Acid Enzymes and Metabolism (13 papers) and Chemical Synthesis and Analysis (10 papers). Dana Ferraris collaborates with scholars based in United States, Czechia and Japan. Dana Ferraris's co-authors include Thomas Lectka, Takashi Tsukamoto, Brandon Young, Camilo Rojas, William J. Drury, Christopher D. Cox, Travis Dudding, Barbara S. Slusher, Andrew E. Taggi and Ajit G. Thomas and has published in prestigious journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and Journal of Neuroscience.

In The Last Decade

Dana Ferraris

67 papers receiving 4.8k citations

Hit Papers

The Metabolic Profile of ... 2012 2026 2016 2021 2012 100 200 300 400 500

Author Peers

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

Author Last Decade Papers Cites
Dana Ferraris 2.2k 1.5k 1.2k 895 536 68 4.9k
Ronald L. Magolda 3.0k 1.4× 687 0.4× 674 0.6× 953 1.1× 193 0.4× 69 5.6k
Satoshi Shuto 3.1k 1.4× 3.1k 2.0× 372 0.3× 342 0.4× 328 0.6× 328 6.2k
Barry Stoddard 6.3k 2.8× 598 0.4× 214 0.2× 398 0.4× 349 0.7× 77 8.2k
Liangren Zhang 2.7k 1.2× 2.3k 1.5× 222 0.2× 453 0.5× 183 0.3× 236 6.1k
Haitao Ji 2.7k 1.2× 1.3k 0.8× 1.1k 0.9× 681 0.8× 198 0.4× 96 4.8k
Yves Gareau 3.5k 1.6× 1.1k 0.7× 468 0.4× 801 0.9× 196 0.4× 49 6.1k
Ching‐Shih Chen 4.7k 2.1× 913 0.6× 683 0.6× 1.0k 1.1× 146 0.3× 144 6.8k
Isaac S. Harris 6.0k 2.7× 434 0.3× 3.6k 3.1× 1.3k 1.5× 529 1.0× 39 9.4k
Marc Labelle 3.6k 1.6× 873 0.6× 448 0.4× 817 0.9× 247 0.5× 40 6.0k
Masatoshi Shibuya 2.7k 1.2× 2.6k 1.7× 563 0.5× 1.1k 1.3× 143 0.3× 144 6.9k

Countries citing papers authored by Dana Ferraris

Since Specialization
Citations

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

Fields of papers citing papers by Dana Ferraris

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dana Ferraris

This figure shows the co-authorship network connecting the top 25 collaborators of Dana Ferraris. A scholar is included among the top collaborators of Dana Ferraris 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 Dana Ferraris. Dana Ferraris 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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