Daniel H. Foil

1.2k total citations
27 papers, 797 citations indexed

About

Daniel H. Foil is a scholar working on Computational Theory and Mathematics, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Daniel H. Foil has authored 27 papers receiving a total of 797 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computational Theory and Mathematics, 9 papers in Molecular Biology and 5 papers in Infectious Diseases. Recurrent topics in Daniel H. Foil's work include Computational Drug Discovery Methods (10 papers), Mosquito-borne diseases and control (4 papers) and Carcinogens and Genotoxicity Assessment (3 papers). Daniel H. Foil is often cited by papers focused on Computational Drug Discovery Methods (10 papers), Mosquito-borne diseases and control (4 papers) and Carcinogens and Genotoxicity Assessment (3 papers). Daniel H. Foil collaborates with scholars based in United States, Brazil and Germany. Daniel H. Foil's co-authors include Sean Ekins, Kimberley M. Zorn, Thomas R. Lane, Eni Minerali, Ana C. Puhl, Stefano Papazian, Deniz Taşdemir, Delphine Parrot, Victor O. Gawriljuk and Daniel A. Todd and has published in prestigious journals such as Environmental Science & Technology, PLoS ONE and Scientific Reports.

In The Last Decade

Daniel H. Foil

26 papers receiving 786 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel H. Foil United States 18 308 276 102 94 84 27 797
Tongan Zhao United States 9 375 1.2× 337 1.2× 80 0.8× 95 1.0× 26 0.3× 12 730
Ana C. Puhl United States 16 378 1.2× 494 1.8× 141 1.4× 165 1.8× 43 0.5× 48 1.0k
Valery Tkachenko United States 14 450 1.5× 470 1.7× 43 0.4× 201 2.1× 83 1.0× 18 1.0k
David Hoksza Czechia 15 407 1.3× 811 2.9× 65 0.6× 125 1.3× 27 0.3× 55 1.2k
Thomas R. Lane United States 22 572 1.9× 549 2.0× 285 2.8× 227 2.4× 121 1.4× 68 1.5k
Kimberley M. Zorn United States 22 672 2.2× 516 1.9× 247 2.4× 255 2.7× 127 1.5× 36 1.5k
Stefano Rensi United States 7 493 1.6× 375 1.4× 28 0.3× 201 2.1× 42 0.5× 10 804
Mélaine A. Kuenemann France 14 518 1.7× 544 2.0× 37 0.4× 270 2.9× 78 0.9× 23 994
Jiayi Yin China 20 289 0.9× 768 2.8× 62 0.6× 62 0.7× 45 0.5× 41 1.2k
Tailong Lei China 13 498 1.6× 445 1.6× 45 0.4× 126 1.3× 17 0.2× 22 879

Countries citing papers authored by Daniel H. Foil

Since Specialization
Citations

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

Fields of papers citing papers by Daniel H. Foil

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel H. Foil. 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 Daniel H. Foil. The network helps show where Daniel H. Foil may publish in the future.

Co-authorship network of co-authors of Daniel H. Foil

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel H. Foil. A scholar is included among the top collaborators of Daniel H. Foil 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 Daniel H. Foil. Daniel H. Foil 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.
Foil, Daniel H., et al.. (2025). Comparative Chemical Space Analysis of Pesticides and Substances with Genotoxicity Data. Chemical Research in Toxicology. 38(11). 1871–1888.
2.
Foil, Daniel H., et al.. (2025). Extension of the EFSA Pesticides Genotoxicity Database. EFSA Supporting Publications. 22(3). 2 indexed citations
3.
Mottin, Melina, Lindsay K. Caesar, G.D. Noske, et al.. (2022). Chalcones from Angelica keiskei (ashitaba) inhibit key Zika virus replication proteins. Bioorganic Chemistry. 120. 105649–105649. 16 indexed citations
4.
Puhl, Ana C., Tammy M. Havener, Daniel H. Foil, et al.. (2022). Multiple approaches to repurposing drugs for neuroblastoma. Bioorganic & Medicinal Chemistry. 73. 117043–117043. 7 indexed citations
5.
Gawriljuk, Victor O., Daniel H. Foil, Ana C. Puhl, et al.. (2021). Development of Machine Learning Models and the Discovery of a New Antiviral Compound against Yellow Fever Virus. Journal of Chemical Information and Modeling. 61(8). 3804–3813. 15 indexed citations
6.
Gawriljuk, Victor O., Ana C. Puhl, Kimberley M. Zorn, et al.. (2021). Machine Learning Models Identify Inhibitors of SARS-CoV-2. Journal of Chemical Information and Modeling. 61(9). 4224–4235. 36 indexed citations
7.
Klein, Jennifer J., Nancy Baker, Daniel H. Foil, et al.. (2021). Using Bibliometric Analysis and Machine Learning to Identify Compounds Binding to Sialidase-1. ACS Omega. 6(4). 3186–3193. 11 indexed citations
8.
Minerali, Eni, Thomas R. Lane, Daniel H. Foil, et al.. (2021). The Antiviral Drug Tilorone Is a Potent and Selective Inhibitor of Acetylcholinesterase. Chemical Research in Toxicology. 34(5). 1296–1307. 22 indexed citations
9.
Ekins, Sean, Melina Mottin, Bruno J. Neves, et al.. (2020). Déjà vu: Stimulating open drug discovery for SARS-CoV-2. Drug Discovery Today. 25(5). 928–941. 66 indexed citations
10.
Brown, Adam R., Keivan A. Ettefagh, Daniel A. Todd, et al.. (2020). Bacterial efflux inhibitors are widely distributed in land plants. Journal of Ethnopharmacology. 267. 113533–113533. 12 indexed citations
11.
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
12.
Lane, Thomas R., Julie Dyall, Daniel H. Foil, et al.. (2020). Repurposing Pyramax®, quinacrine and tilorone as treatments for Ebola virus disease. Antiviral Research. 182. 104908–104908. 22 indexed citations
13.
Zhang, Xiaohong, Joseph L. Jilek, Erin Q. Jennings, et al.. (2020). Predicting Drug Interactions with Human Equilibrative Nucleoside Transporters 1 and 2 Using Functional Knockout Cell Lines and Bayesian Modeling. Molecular Pharmacology. 99(2). 147–162. 19 indexed citations
14.
Minerali, Eni, et al.. (2020). Machine Learning for Discovery of GSK3β Inhibitors. ACS Omega. 5(41). 26551–26561. 35 indexed citations
15.
Minerali, Eni, Daniel H. Foil, Kimberley M. Zorn, Thomas R. Lane, & Sean Ekins. (2020). Comparing Machine Learning Algorithms for Predicting Drug-Induced Liver Injury (DILI). Molecular Pharmaceutics. 17(7). 2628–2637. 59 indexed citations
16.
Minerali, Eni, Daniel H. Foil, Kimberley M. Zorn, & Sean Ekins. (2020). Evaluation of Assay Central Machine Learning Models for Rat Acute Oral Toxicity Prediction. ACS Sustainable Chemistry & Engineering. 8(42). 16020–16027. 21 indexed citations
17.
Zorn, Kimberley M., Daniel H. Foil, Thomas R. Lane, et al.. (2020). Comparing Machine Learning Models for Aromatase (P450 19A1). Environmental Science & Technology. 54(23). 15546–15555. 11 indexed citations
18.
Foil, Daniel H., Adam R. Brown, Daniel A. Todd, et al.. (2017). Secondary metabolites from the leaves of the medicinal plant goldenseal ( Hydrastis canadensis ). Phytochemistry Letters. 20. 54–60. 27 indexed citations
19.
Ekladious, Iriny, Daniel H. Foil, Daniel A. Todd, et al.. (2017). Synthesis of poly(1,2-glycerol carbonate)–paclitaxel conjugates and their utility as a single high-dose replacement for multi-dose treatment regimens in peritoneal cancer. Chemical Science. 8(12). 8443–8450. 25 indexed citations
20.
Brown, Adam R., Keivan A. Ettefagh, Daniel A. Todd, et al.. (2015). A Mass Spectrometry-Based Assay for Improved Quantitative Measurements of Efflux Pump Inhibition. PLoS ONE. 10(5). e0124814–e0124814. 55 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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