Nigel Greene

4.0k total citations · 1 hit paper
56 papers, 2.7k citations indexed

About

Nigel Greene is a scholar working on Computational Theory and Mathematics, Molecular Biology and Pharmacology. According to data from OpenAlex, Nigel Greene has authored 56 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Computational Theory and Mathematics, 15 papers in Molecular Biology and 15 papers in Pharmacology. Recurrent topics in Nigel Greene's work include Computational Drug Discovery Methods (38 papers), Pharmacogenetics and Drug Metabolism (15 papers) and Animal testing and alternatives (10 papers). Nigel Greene is often cited by papers focused on Computational Drug Discovery Methods (38 papers), Pharmacogenetics and Drug Metabolism (15 papers) and Animal testing and alternatives (10 papers). Nigel Greene collaborates with scholars based in United States, United Kingdom and Sweden. Nigel Greene's co-authors include David A. Price, Travis T. Wager, Julian Blagg, Russell Naven, Philip N. Judson, Carol A. Marchant, J. J. Langowski, Falgun Shah, Yvonne Will and Rajesh Devraj and has published in prestigious journals such as PLoS ONE, Nature Methods and Advanced Drug Delivery Reviews.

In The Last Decade

Nigel Greene

54 papers receiving 2.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Physiochemical drug properties associated with in vivo toxicological outcomes

2008 675 citations Julian Blagg, David A. Price et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nigel Greene United States	26	1.3k	945	603	343	312	56	2.7k
Hong Fang United States	40	1.6k 1.2×	2.0k 2.1×	747 1.2×	294 0.9×	290 0.9×	83	4.8k
Hongbin Yang China	28	1.5k 1.1×	1.3k 1.3×	419 0.7×	512 1.5×	154 0.5×	70	3.2k
Alexander Sedykh United States	28	1.3k 1.0×	782 0.8×	311 0.5×	141 0.4×	145 0.5×	51	2.3k
Scott Boyer Sweden	32	1.1k 0.9×	1.0k 1.1×	333 0.6×	149 0.4×	237 0.8×	69	2.3k
Chihae Yang United States	25	1.9k 1.4×	1.2k 1.2×	234 0.4×	343 1.0×	242 0.8×	71	3.4k
Lothar Terfloth Germany	14	1.2k 0.9×	1.1k 1.2×	161 0.3×	306 0.9×	195 0.6×	21	2.3k
Vijay K. Gombar United States	18	1.7k 1.3×	761 0.8×	162 0.3×	714 2.1×	458 1.5×	34	2.7k
Zengrui Wu China	24	1.8k 1.4×	1.6k 1.7×	543 0.9×	684 2.0×	126 0.4×	70	3.5k
Jacques Hamon Switzerland	16	1.6k 1.2×	1.7k 1.7×	533 0.9×	258 0.8×	118 0.4×	25	3.0k

Countries citing papers authored by Nigel Greene

Since Specialization

Citations

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

Fields of papers citing papers by Nigel Greene

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nigel Greene

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

All Works

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20 of 20 papers shown

Seal, Srijit, Maria‐Anna Trapotsi, Vigneshwari Subramanian, et al.. (2025). PKSmart: an open-source computational model to predict intravenous pharmacokinetics of small molecules. Journal of Cheminformatics. 17(1). 147–147.

Seal, Srijit, Maria‐Anna Trapotsi, Ola Spjuth, et al.. (2024). Cell Painting: a decade of discovery and innovation in cellular imaging. Nature Methods. 22(2). 254–268. 18 indexed citations

Snodin, David J., Alejandra Trejo‐Martin, David J. Ponting, et al.. (2024). Mechanisms of Nitrosamine Mutagenicity and Their Relationship to Rodent Carcinogenic Potency. Chemical Research in Toxicology. 37(2). 181–198. 28 indexed citations

Obrezanova, Olga, Thomas M. Whitehead, Andreas Bender, et al.. (2022). Prediction of In Vivo Pharmacokinetic Parameters and Time–Exposure Curves in Rats Using Machine Learning from the Chemical Structure. Molecular Pharmaceutics. 19(5). 1488–1504. 46 indexed citations

Briggs, Katharine, Robert Thomas, G. Smith, et al.. (2022). Statistical analysis of preclinical inter-species concordance of histopathological findings in the eTOX database. Regulatory Toxicology and Pharmacology. 138. 105308–105308. 2 indexed citations

Miljković, Filip, Olga Obrezanova, Beth Williamson, et al.. (2021). Machine Learning Models for Human In Vivo Pharmacokinetic Parameters with In-House Validation. Molecular Pharmaceutics. 18(12). 4520–4530. 59 indexed citations

Sturm, Noé, Andreas Mayr, Vladimir Chupakhin, et al.. (2020). Industry-scale application and evaluation of deep learning for drug target prediction. Journal of Cheminformatics. 12(1). 26–26. 29 indexed citations

Guzzie‐Peck, Peggy, Matthew S. Bogdanffy, Yvonne Will, et al.. (2017). Current nonclinical testing paradigms in support of safe clinical trials: An IQ Consortium DruSafe perspective. Regulatory Toxicology and Pharmacology. 87. S1–S15. 25 indexed citations

Williams, Richard V., Alexander Amberg, Alessandro Brigo, et al.. (2016). It's difficult, but important, to make negative predictions. Regulatory Toxicology and Pharmacology. 76. 79–86. 43 indexed citations

10.

Greene, Nigel, Krista L. Dobo, Michelle Kenyon, et al.. (2015). A practical application of two in silico systems for identification of potentially mutagenic impurities. Regulatory Toxicology and Pharmacology. 72(2). 335–349. 32 indexed citations

11.

Barber, Chris, Thierry Hanser, Jonathan D. Vessey, et al.. (2015). Evaluation of a statistics-based Ames mutagenicity QSAR model and interpretation of the results obtained. Regulatory Toxicology and Pharmacology. 76. 7–20. 35 indexed citations

12.

Shah, Falgun, Louis Leung, Hugh A. Barton, et al.. (2015). Setting Clinical Exposure Levels of Concern for Drug-Induced Liver Injury (DILI) Using Mechanisticin vitroAssays. Toxicological Sciences. 147(2). 500–514. 106 indexed citations

13.

Shah, Falgun, et al.. (2014). Finding the rules for successful drug optimisation. Drug Discovery Today. 19(5). 680–687. 26 indexed citations

14.

Dobo, Krista L., Nigel Greene, Charlotta Fred, et al.. (2012). In silico methods combined with expert knowledge rule out mutagenic potential of pharmaceutical impurities: An industry survey. Regulatory Toxicology and Pharmacology. 62(3). 449–455. 62 indexed citations

15.

Wang, Xiangyun & Nigel Greene. (2012). Comparing Measures of Promiscuity and Exploring Their Relationship to Toxicity. Molecular Informatics. 31(2). 145–159. 23 indexed citations

16.

Greene, Nigel, et al.. (2009). A current practice for predicting ocular toxicity of systemically delivered drugs. Cutaneous and Ocular Toxicology. 28(1). 1–18. 12 indexed citations

17.

Greene, Nigel & Russell Naven. (2009). Early toxicity screening strategies.. PubMed. 12(1). 90–7. 25 indexed citations

18.

Price, David A., Julian Blagg, Lyn H. Jones, Nigel Greene, & Travis T. Wager. (2009). Physicochemical drug properties associated within vivotoxicological outcomes: a review. Expert Opinion on Drug Metabolism & Toxicology. 5(8). 921–931. 107 indexed citations

19.

Greene, Nigel, Philip N. Judson, J. J. Langowski, & Carol A. Marchant. (1999). Knowledge-Based Expert Systems for Toxicity and Metabolism Prediction: DEREK, StAR and METEOR. SAR and QSAR in environmental research. 10(2-3). 299–314. 196 indexed citations

20.

Greene, Nigel, et al.. (1998). In vitro elution of tobramycin and vancomycin polymethylmethacrylate beads and spacers from Simplex and Palacos.. PubMed. 27(3). 201–5. 76 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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