Stefano Forli

17.3k citations
96 papers · 10.7k indexed · 8 hit papers · h-index 37

Stefano Forli

88 papers receiving 10.6k citations

Hit Papers

Accelerating A uto D ock ...192201020262015202010002.0k3.0k

Peers

Stefano Forli
Comparison fields: 5 of 168
  • Computational Theory and Mathematics 2.6k
  • Organic Chemistry 2.9k
  • Molecular Biology 6.1k
  • Toxicology 225
  • Pharmacology 545
Replace Weiliang Zhu with:
Weiliang Zhu China
Tyler Day United States
Jeremy R. Greenwood United States
Kaixian Chen China
Bernd Kuhn Switzerland
David B. Ascher Australia
Jonathan B. Baell Australia
Leah L. Frye United States
Stefano Moro Italy
Jason K. Perry United States
Stefano Forli relative to Weiliang Zhu China Weiliang Zhu's profile →
Citations per field
00.5×3.3×
Weiliang Zhu · 1×
Citations per year

Countries citing papers authored by Stefano Forli

Since Specialization
Citations

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

Fields of papers citing papers by Stefano Forli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Stefano Forli, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stefano Forli Line = papers co-authored together Stefano Forli links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20250
4 202417
5 20243
6 202414
7 202313
8 202231
9
Accelerating A uto D ock 4 with GPUs and Gradient-Based Local Searchbreakdown →
2021192
10 202115
11 20219
12 2020141
13 2020213
14 202044
15
SuFEx-enabled, agnostic discovery of covalent inhibitors of human neutrophil elastasebreakdown →
2019157
16 201930
17 201954
18 201953
19
“Inverse Drug Discovery” Strategy To Identify Proteins That Are Targeted by Latent Electrophiles As Exemplified by Aryl Fluorosulfatesbreakdown →
2017237
20 201443

About Stefano Forli

Stefano Forli is a scholar working on Virology, Computational Theory and Mathematics and Molecular Biology, having authored 96 papers that have together received 10.7k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (31 papers), Protein Structure and Dynamics (26 papers), Click Chemistry and Applications (15 papers), HIV/AIDS drug development and treatment (13 papers), HIV Research and Treatment (13 papers), Chemical Synthesis and Analysis (12 papers), Monoclonal and Polyclonal Antibodies Research (9 papers) and RNA and protein synthesis mechanisms (7 papers). The work is most often cited by research in Computational Theory and Mathematics (2.6k citations), Organic Chemistry (2.9k citations) and Molecular Biology (6.1k citations). Stefano Forli has collaborated with scholars based in United States, Italy and Germany. Frequent co-authors include Diogo Santos‐Martins, Andreas F. Tillack, Jérôme Eberhardt, Arthur J. Olson, David S. Goodsell, Michel F. Sanner, Michael E. Pique, Ruth Huey, Benjamin F. Cravatt and Keriann M. Backus. Their work appears in journals such as Journal of Chemical Information and Modeling, Journal of Medicinal Chemistry, Journal of Computer-Aided Molecular Design, Journal of Chemical Theory and Computation and Protein Science.

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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