James W. Firman

783 total citations
38 papers, 487 citations indexed

About

James W. Firman is a scholar working on Computational Theory and Mathematics, Small Animals and Molecular Biology. According to data from OpenAlex, James W. Firman has authored 38 papers receiving a total of 487 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computational Theory and Mathematics, 9 papers in Small Animals and 9 papers in Molecular Biology. Recurrent topics in James W. Firman's work include Computational Drug Discovery Methods (25 papers), Animal testing and alternatives (9 papers) and Chemistry and Chemical Engineering (8 papers). James W. Firman is often cited by papers focused on Computational Drug Discovery Methods (25 papers), Animal testing and alternatives (9 papers) and Chemistry and Chemical Engineering (8 papers). James W. Firman collaborates with scholars based in United Kingdom, United States and Canada. James W. Firman's co-authors include M Cronin, Judith C. Madden, Steven J. Enoch, Gopal Pawar, Claire L. Mellor, Chihae Yang, Nicoleta Sp̂înu, Richard Marchese Robinson, Steven D. Webb and Mathieu Vinken and has published in prestigious journals such as Environmental Science & Technology, PLoS ONE and Food and Chemical Toxicology.

In The Last Decade

James W. Firman

35 papers receiving 473 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James W. Firman United Kingdom 14 216 131 117 114 71 38 487
Steve Gutsell United Kingdom 15 255 1.2× 216 1.6× 122 1.0× 160 1.4× 88 1.2× 33 649
Claire M. Ellison United Kingdom 11 242 1.1× 158 1.2× 77 0.7× 91 0.8× 55 0.8× 14 469
Claire L. Mellor United Kingdom 12 209 1.0× 90 0.7× 109 0.9× 122 1.1× 68 1.0× 19 477
Arianna Bassan Italy 13 245 1.1× 135 1.0× 71 0.6× 96 0.8× 57 0.8× 30 501
Chanita Kuseva Bulgaria 14 262 1.2× 151 1.2× 164 1.4× 79 0.7× 88 1.2× 20 582
Giuseppa Raitano Italy 13 251 1.2× 109 0.8× 45 0.4× 120 1.1× 42 0.6× 27 437
Atanas Chapkanov Bulgaria 8 172 0.8× 99 0.8× 70 0.6× 56 0.5× 55 0.8× 13 328
Kirk Arvidson United States 11 223 1.0× 132 1.0× 81 0.7× 98 0.9× 54 0.8× 13 444
Jay Russell Niemelä Denmark 10 294 1.4× 186 1.4× 106 0.9× 103 0.9× 66 0.9× 16 631
Tommy Cathey United States 7 163 0.8× 211 1.6× 77 0.7× 156 1.4× 44 0.6× 8 467

Countries citing papers authored by James W. Firman

Since Specialization
Citations

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

Fields of papers citing papers by James W. Firman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James W. Firman. 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 James W. Firman. The network helps show where James W. Firman may publish in the future.

Co-authorship network of co-authors of James W. Firman

This figure shows the co-authorship network connecting the top 25 collaborators of James W. Firman. A scholar is included among the top collaborators of James W. Firman 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 James W. Firman. James W. Firman 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.
Firman, James W., et al.. (2025). Conservative consensus QSAR approach for the prediction of rat acute oral toxicity. Computational Toxicology. 35. 100374–100374.
2.
Leme, Daniela Morais, et al.. (2025). Challenges and opportunities of read-across for the tumor promotion effects of microcystins. Regulatory Toxicology and Pharmacology. 163. 105938–105938.
3.
Firman, James W., Alan R. Boobis, Heli M. Hollnagel, et al.. (2024). Evaluating the consistency of judgments derived through both in silico and expert application of the Cramer classification scheme. Food and Chemical Toxicology. 194. 115070–115070. 1 indexed citations
4.
Cronin, M, Hassan Basiri, Steven J. Enoch, et al.. (2024). The predictivity of QSARs for toxicity: Recommendations for improving model performance. Computational Toxicology. 33. 100338–100338. 10 indexed citations
5.
Firman, James W., et al.. (2024). Analysis of implicit and explicit uncertainties in QSAR prediction of chemical toxicity: A case study of neurotoxicity. Regulatory Toxicology and Pharmacology. 154. 105716–105716. 3 indexed citations
6.
Galbiati, Valentina, Daniela Fiori Gradia, Anderson Joel Martino‐Andrade, et al.. (2024). The evaluation of skin sensitization potential of the UVCB substance diisopentyl phthalate by in silico and in vitro methods. Archives of Toxicology. 98(7). 2153–2171. 4 indexed citations
7.
Firman, James W., et al.. (2024). A framework for categorizing sources of uncertainty in in silico toxicology methods: Considerations for chemical toxicity predictions. Regulatory Toxicology and Pharmacology. 154. 105737–105737. 2 indexed citations
8.
Cronin, M, Katharine Briggs, Steven J. Enoch, et al.. (2023). Making in silico predictive models for toxicology FAIR. Regulatory Toxicology and Pharmacology. 140. 105385–105385. 17 indexed citations
9.
Yang, Chihae, James F. Rathman, Monika Batke, et al.. (2023). Update of the Cancer Potency Database (CPDB) to enable derivations of Thresholds of Toxicological Concern (TTC) for cancer potency. Food and Chemical Toxicology. 182. 114182–114182. 4 indexed citations
10.
11.
Cronin, M, Mark Bonnell, Bruno Campos, et al.. (2022). A scheme to evaluate structural alerts to predict toxicity – Assessing confidence by characterising uncertainties. Regulatory Toxicology and Pharmacology. 135. 105249–105249. 13 indexed citations
12.
Firman, James W., Michael R. Goldsmith, Chris Grulke, et al.. (2021). A Systematic Review of Published Physiologically-based Kinetic Models and an Assessment of their Chemical Space Coverage. Alternatives to Laboratory Animals. 49(5). 197–208. 25 indexed citations
13.
Enoch, Steven J., et al.. (2021). Determination of “fitness-for-purpose” of quantitative structure-activity relationship (QSAR) models to predict (eco-)toxicological endpoints for regulatory use. Regulatory Toxicology and Pharmacology. 123. 104956–104956. 17 indexed citations
14.
Sp̂înu, Nicoleta, et al.. (2021). Derivation, characterisation and analysis of an adverse outcome pathway network for human hepatotoxicity. Toxicology. 459. 152856–152856. 26 indexed citations
15.
Firman, James W., et al.. (2020). A Robust, Mechanistically Based In Silico Structural Profiler for Hepatic Cholestasis. Chemical Research in Toxicology. 34(2). 641–655. 4 indexed citations
16.
Mellor, Claire L., Knut Erik Tollefsen, Carlie A. LaLone, M Cronin, & James W. Firman. (2020). In Silico Identification of Chemicals Capable of Binding to the Ecdysone Receptor. Environmental Toxicology and Chemistry. 39(7). 1438–1450. 7 indexed citations
17.
Firman, James W., Ans Punt, M Cronin, et al.. (2020). Exploring the Potential of ToxCast Data in Supporting Read-Across for Evaluation of Food Chemical Safety. Chemical Research in Toxicology. 34(2). 300–312. 14 indexed citations
18.
Pawar, Gopal, et al.. (2019). In Silico Toxicology Data Resources to Support Read-Across and (Q)SAR. Frontiers in Pharmacology. 10. 561–561. 47 indexed citations
19.
Mellor, Claire L., Richard Marchese Robinson, Steven J. Enoch, et al.. (2018). Molecular fingerprint-derived similarity measures for toxicological read-across: Recommendations for optimal use. Regulatory Toxicology and Pharmacology. 101. 121–134. 71 indexed citations
20.
Enoch, Steven J., Claire L. Mellor, Gopal Pawar, et al.. (2018). A critical review of adverse effects to the kidney: mechanisms, data sources, andin silicotools to assist prediction. Expert Opinion on Drug Metabolism & Toxicology. 14(12). 1225–1253. 7 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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