David S. Perlin

103 total papers · 4.0k total citations
52 papers, 1.5k citations indexed

About

David S. Perlin is a scholar working on Infectious Diseases, Epidemiology and Molecular Biology. According to data from OpenAlex, David S. Perlin has authored 52 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Infectious Diseases, 29 papers in Epidemiology and 7 papers in Molecular Biology. Recurrent topics in David S. Perlin's work include Antifungal resistance and susceptibility (29 papers), Fungal Infections and Studies (22 papers) and COVID-19 Clinical Research Studies (8 papers). David S. Perlin is often cited by papers focused on Antifungal resistance and susceptibility (29 papers), Fungal Infections and Studies (22 papers) and COVID-19 Clinical Research Studies (8 papers). David S. Perlin collaborates with scholars based in United States, Netherlands and Türkiye. David S. Perlin's co-authors include Amir Arastehfar, Milena Kordalewska, Mohammad Taghi Hedayati, Martin Hoenigl, Macit İlkit, Farnaz Daneshnia, Agostinho Carvalho, Steven Park, M. Hong Nguyen and Mihai G. Netea and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

David S. Perlin

47 papers receiving 1.5k citations

Hit Papers

The importance of antimic... 2022 2026 2023 2024 2022 2023 40 80 120

Author Peers

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

Author Last Decade Papers Cites
David S. Perlin 1.0k 699 340 183 119 52 1.5k
E. Nagy 693 0.7× 725 1.0× 402 1.2× 131 0.7× 88 0.7× 52 2.1k
Alireza Abdolrasouli 1.4k 1.3× 887 1.3× 234 0.7× 75 0.4× 80 0.7× 56 1.9k
Jeffrey M. Rybak 1.3k 1.3× 901 1.3× 345 1.0× 401 2.2× 111 0.9× 35 1.9k
László Majoros 979 1.0× 660 0.9× 367 1.1× 214 1.2× 49 0.4× 96 1.4k
C C Knapp 1.1k 1.1× 874 1.3× 192 0.6× 372 2.0× 115 1.0× 49 1.7k
Soo Hyun Kim 1.7k 1.6× 1.4k 2.0× 339 1.0× 101 0.6× 111 0.9× 85 2.3k
Jeffrey D. Jenks 1.7k 1.7× 1.3k 1.9× 193 0.6× 153 0.8× 94 0.8× 50 2.1k
Joveria Farooqi 1.6k 1.6× 1.3k 1.9× 200 0.6× 112 0.6× 190 1.6× 75 2.0k
João Nóbrega de Almeida 1.4k 1.3× 1.2k 1.7× 219 0.6× 135 0.7× 127 1.1× 76 1.8k
Aspasia Katragkou 871 0.9× 697 1.0× 223 0.7× 157 0.9× 67 0.6× 41 1.3k

Countries citing papers authored by David S. Perlin

Since Specialization
Citations

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

Fields of papers citing papers by David S. Perlin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David S. Perlin. 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 David S. Perlin. The network helps show where David S. Perlin may publish in the future.

Co-authorship network of co-authors of David S. Perlin

This figure shows the co-authorship network connecting the top 25 collaborators of David S. Perlin. A scholar is included among the top collaborators of David S. Perlin 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 David S. Perlin. David S. Perlin 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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