Danielle M. Agnello

10 total papers · 1.1k total citations
4 papers, 829 citations indexed

About

Danielle M. Agnello is a scholar working on Molecular Medicine, Endocrinology and Molecular Biology. According to data from OpenAlex, Danielle M. Agnello has authored 4 papers receiving a total of 829 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Medicine, 4 papers in Endocrinology and 2 papers in Molecular Biology. Recurrent topics in Danielle M. Agnello's work include Vibrio bacteria research studies (4 papers), Antibiotic Resistance in Bacteria (4 papers) and Bacterial biofilms and quorum sensing (2 papers). Danielle M. Agnello is often cited by papers focused on Vibrio bacteria research studies (4 papers), Antibiotic Resistance in Bacteria (4 papers) and Bacterial biofilms and quorum sensing (2 papers). Danielle M. Agnello collaborates with scholars based in United States, Sweden and United Kingdom. Danielle M. Agnello's co-authors include Joseph D. Mougous, Alistair B. Russell, Paul A. Wiggins, Michele LeRoux, Takahiko Ishikawa, Sun Nyunt Wai, Rachel D. Hood, Benjamin T. Andrews, Carlos E. Catalano and Julie M. Silverman and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Molecular Cell.

In The Last Decade

Danielle M. Agnello

4 papers receiving 825 citations

Author Peers

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

Author Last Decade Papers Cites
Danielle M. Agnello 696 340 262 208 72 4 829
Kevin G. Hicks 680 1.0× 303 0.9× 408 1.6× 262 1.3× 112 1.6× 8 1.0k
Brittany N. Harding 526 0.8× 238 0.7× 391 1.5× 307 1.5× 73 1.0× 7 937
Francesca Romana Cianfanelli 445 0.6× 180 0.5× 258 1.0× 190 0.9× 81 1.1× 11 730
Brent S. Weber 508 0.7× 622 1.8× 428 1.6× 141 0.7× 56 0.8× 15 944
Thibault G. Sana 555 0.8× 324 1.0× 433 1.7× 172 0.8× 50 0.7× 16 865
Laura Monlezun 368 0.5× 371 1.1× 425 1.6× 207 1.0× 59 0.8× 18 866
G P Huntley-Carter 485 0.7× 204 0.6× 222 0.8× 116 0.6× 78 1.1× 8 840
Benjamin Kostiuk 618 0.9× 266 0.8× 201 0.8× 117 0.6× 40 0.6× 11 741
Katy M. Clemmer 272 0.4× 363 1.1× 547 2.1× 158 0.8× 40 0.6× 12 756
Takahiko Ishikawa 607 0.9× 240 0.7× 336 1.3× 151 0.7× 82 1.1× 16 950

Countries citing papers authored by Danielle M. Agnello

Since Specialization
Citations

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

Fields of papers citing papers by Danielle M. Agnello

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danielle M. Agnello

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