Stephen J. Capuzzi

2.2k total citations
27 papers, 890 citations indexed

About

Stephen J. Capuzzi is a scholar working on Molecular Biology, Computational Theory and Mathematics and Organic Chemistry. According to data from OpenAlex, Stephen J. Capuzzi has authored 27 papers receiving a total of 890 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 10 papers in Computational Theory and Mathematics and 3 papers in Organic Chemistry. Recurrent topics in Stephen J. Capuzzi's work include Computational Drug Discovery Methods (10 papers), Machine Learning in Materials Science (3 papers) and Animal testing and alternatives (3 papers). Stephen J. Capuzzi is often cited by papers focused on Computational Drug Discovery Methods (10 papers), Machine Learning in Materials Science (3 papers) and Animal testing and alternatives (3 papers). Stephen J. Capuzzi collaborates with scholars based in United States, Brazil and Ukraine. Stephen J. Capuzzi's co-authors include Alexander Tropsha, Eugene Muratov, Vinícius M. Alves, Carolina Horta Andrade, Regina Politi, Olexandr Isayev, Rodolpho C. Braga, Thomas Thornton, Denis Fourches and Daniel Korn and has published in prestigious journals such as Scientific Reports, Journal of Medicinal Chemistry and Green Chemistry.

In The Last Decade

Stephen J. Capuzzi

24 papers receiving 883 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Stephen J. Capuzzi United States 17 449 425 124 110 82 27 890
Terry R. Van Vleet United States 20 201 0.4× 609 1.4× 36 0.3× 50 0.5× 67 0.8× 35 1.5k
Dolores Diaz United States 15 203 0.5× 618 1.5× 36 0.3× 47 0.4× 31 0.4× 22 1.3k
Jia Jia Singapore 5 300 0.7× 550 1.3× 66 0.5× 65 0.6× 77 0.9× 13 911
Hui Wen Ng United States 16 182 0.4× 289 0.7× 31 0.3× 50 0.5× 28 0.3× 23 652
Freddy Van Goethem Belgium 17 92 0.2× 276 0.6× 60 0.5× 33 0.3× 32 0.4× 31 939
Junfeng Zhu China 16 110 0.2× 241 0.6× 26 0.2× 40 0.4× 43 0.5× 27 671
Tongan Zhao United States 9 375 0.8× 337 0.8× 95 0.8× 17 0.2× 48 0.6× 12 730
Philippe Vanparys Belgium 22 100 0.2× 471 1.1× 50 0.4× 29 0.3× 30 0.4× 33 1.3k
Mohan Rao United States 7 153 0.3× 215 0.5× 32 0.3× 21 0.2× 19 0.2× 13 446
Julia H. Fentem United Kingdom 22 203 0.5× 226 0.5× 27 0.2× 43 0.4× 60 0.7× 56 1.5k

Countries citing papers authored by Stephen J. Capuzzi

Since Specialization
Citations

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

Fields of papers citing papers by Stephen J. Capuzzi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen J. Capuzzi. 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 Stephen J. Capuzzi. The network helps show where Stephen J. Capuzzi may publish in the future.

Co-authorship network of co-authors of Stephen J. Capuzzi

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen J. Capuzzi. A scholar is included among the top collaborators of Stephen J. Capuzzi 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 Stephen J. Capuzzi. Stephen J. Capuzzi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Hickey, Anthony J., Alexander Tropsha, Eugene Muratov, et al.. (2024). Knowledge-based approaches to drug discovery for rare diseases. UNC Libraries.
2.
3.
Alves, Vinícius M., Adam Yasgar, Ganesha Rai, et al.. (2023). Lies and Liabilities: Computational Assessment of High-Throughput Screening Hits to Identify Artifact Compounds. Journal of Medicinal Chemistry. 66(18). 12828–12839. 5 indexed citations
4.
Capuzzi, Stephen J., Dmytro S. Radchenko, Olena Savych, et al.. (2022). Generative and reinforcement learning approaches for the automated de novo design of bioactive compounds. Communications Chemistry. 5(1). 129–129. 59 indexed citations
5.
Korn, Daniel, Vinícius M. Alves, Joyce Villa Verde Bastos Borba, et al.. (2022). Defining clinical outcome pathways. Drug Discovery Today. 27(6). 1671–1678. 9 indexed citations
6.
Alves, Vinícius M., Daniel Korn, Stephen J. Capuzzi, et al.. (2021). Knowledge-based approaches to drug discovery for rare diseases. Drug Discovery Today. 27(2). 490–502. 26 indexed citations
7.
Havener, Tammy M., Kimberley M. Zorn, Daniel H. Foil, et al.. (2020). Synergistic drug combinations and machine learning for drug repurposing in chordoma. Scientific Reports. 10(1). 12982–12982. 32 indexed citations
8.
Ferguson, Fleur M., Yan Liu, Wayne Harshbarger, et al.. (2020). Synthesis and Structure–Activity Relationships of DCLK1 Kinase Inhibitors Based on a 5,11-Dihydro-6H-benzo[e]pyrimido[5,4-b][1,4]diazepin-6-one Scaffold. Journal of Medicinal Chemistry. 63(14). 7817–7826. 15 indexed citations
9.
Alves, Vinícius M., Stephen J. Capuzzi, Rodolpho C. Braga, et al.. (2020). SCAM Detective: Accurate Predictor of Small, Colloidally Aggregating Molecules. Journal of Chemical Information and Modeling. 60(8). 4056–4063. 25 indexed citations
10.
Capuzzi, Stephen J., et al.. (2020). Phantom PAINS: Problems with the Utility of Alerts for P an- A ssay IN terference Compound S. UNC Libraries. 1 indexed citations
11.
Li, Jizhen, Ling‐Chu Chang, Pei‐Ling Hsu, et al.. (2019). Design, synthesis and evaluation of antiproliferative activity of fluorinated betulinic acid. Bioorganic & Medicinal Chemistry. 27(13). 2871–2882. 9 indexed citations
12.
Asquith, Christopher R. M., Benedict‐Tilman Berger, James M. Bennett, et al.. (2019). SGC-GAK-1: A Chemical Probe for Cyclin G Associated Kinase (GAK). Journal of Medicinal Chemistry. 62(5). 2830–2836. 45 indexed citations
13.
Capuzzi, Stephen J., Wei Sun, Eugene Muratov, et al.. (2018). Computer-Aided Discovery and Characterization of Novel Ebola Virus Inhibitors. Journal of Medicinal Chemistry. 61(8). 3582–3594. 27 indexed citations
14.
Capuzzi, Stephen J., Thomas Thornton, Nancy Baker, et al.. (2018). Chemotext: A Publicly Available Web Server for Mining Drug–Target–Disease Relationships in PubMed. Journal of Chemical Information and Modeling. 58(2). 212–218. 32 indexed citations
15.
Alves, Vinícius M., Alexander Golbraikh, Stephen J. Capuzzi, et al.. (2018). Multi-Descriptor Read Across (MuDRA): A Simple and Transparent Approach for Developing Accurate Quantitative Structure–Activity Relationship Models. Journal of Chemical Information and Modeling. 58(6). 1214–1223. 40 indexed citations
16.
O’Banion, Colin P., Melanie A. Priestman, Robert M. Hughes, et al.. (2017). Design and Profiling of a Subcellular Targeted Optogenetic cAMP-Dependent Protein Kinase. Cell chemical biology. 25(1). 100–109.e8. 30 indexed citations
17.
Capuzzi, Stephen J., et al.. (2017). Chembench: A Publicly Accessible, Integrated Cheminformatics Portal. Journal of Chemical Information and Modeling. 57(2). 105–108. 42 indexed citations
18.
Capuzzi, Stephen J., et al.. (2016). QSAR Modeling of Tox21 Challenge Stress Response and Nuclear Receptor Signaling Toxicity Assays. Frontiers in Environmental Science. 4. 60 indexed citations
19.
Belinsky, Martin G., Lori Rink, Kathy Q. Cai, et al.. (2015). Somatic loss of function mutations in neurofibromin 1 and MYC associated factor X genes identified by exome-wide sequencing in a wild-type GIST case. BMC Cancer. 15(1). 887–887. 26 indexed citations
20.
Clark, Peter A., et al.. (2012). Slow-sand water filter: Design, implementation, accessibility and sustainability in developing countries. Medical Science Monitor. 18(7). RA105–RA117. 21 indexed citations

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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