Mark Nelms

492 total citations
29 papers, 321 citations indexed

About

Mark Nelms is a scholar working on Computational Theory and Mathematics, Health, Toxicology and Mutagenesis and Electrical and Electronic Engineering. According to data from OpenAlex, Mark Nelms has authored 29 papers receiving a total of 321 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computational Theory and Mathematics, 12 papers in Health, Toxicology and Mutagenesis and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Mark Nelms's work include Computational Drug Discovery Methods (14 papers), Effects and risks of endocrine disrupting chemicals (8 papers) and Agricultural safety and regulations (3 papers). Mark Nelms is often cited by papers focused on Computational Drug Discovery Methods (14 papers), Effects and risks of endocrine disrupting chemicals (8 papers) and Agricultural safety and regulations (3 papers). Mark Nelms collaborates with scholars based in United States, United Kingdom and Belgium. Mark Nelms's co-authors include Grace Patlewicz, Stephen W. Edwards, Steven J. Enoch, M Cronin, Judith C. Madden, Noffisat O. Oki, Holly M. Mortensen, Shannon Bell, Claire L. Mellor and Kellie A. Fay and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and The Science of The Total Environment.

In The Last Decade

Mark Nelms

27 papers receiving 315 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mark Nelms United States	12	140	106	80	76	35	29	321
Yuki Sakuratani Japan	10	134 1.0×	145 1.4×	49 0.6×	68 0.9×	58 1.7×	23	360
Nicoleta Sp̂înu United Kingdom	9	102 0.7×	106 1.0×	56 0.7×	65 0.9×	25 0.7×	15	281
Claire L. Mellor United Kingdom	12	209 1.5×	90 0.8×	122 1.5×	109 1.4×	11 0.3×	19	477
Sunil Kulkarni Canada	10	106 0.8×	74 0.7×	54 0.7×	42 0.6×	22 0.6×	38	270
Elton Zvinavashe Netherlands	8	170 1.2×	139 1.3×	48 0.6×	48 0.6×	42 1.2×	8	318
Heather L. Ciallella United States	8	277 2.0×	66 0.6×	168 2.1×	35 0.5×	14 0.4×	11	460
Nicholas Ball United States	15	233 1.7×	209 2.0×	116 1.4×	256 3.4×	42 1.2×	34	708
C. Eric Hack United States	12	51 0.4×	156 1.5×	36 0.5×	33 0.4×	27 0.8×	22	369
Oliver Sacher Germany	10	209 1.5×	55 0.5×	182 2.3×	47 0.6×	16 0.5×	15	388
Clemens Wittwehr Italy	9	115 0.8×	89 0.8×	83 1.0×	65 0.9×	23 0.7×	20	329

Countries citing papers authored by Mark Nelms

Since Specialization

Citations

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

Fields of papers citing papers by Mark Nelms

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Nelms

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Nelms. A scholar is included among the top collaborators of Mark Nelms 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 Mark Nelms. Mark Nelms 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

Nelms, Mark, Caroline Ring, Danni L. Harris, et al.. (2024). Chemistry domain of applicability evaluation against existing estrogen receptor high-throughput assay-based activity models. SHILAP Revista de lepidopterología. 6. 1346767–1346767. 1 indexed citations

Edwards, Stephen W., Mark Nelms, Caroline Ring, et al.. (2024). Optimizing androgen receptor prioritization using high-throughput assay-based activity models. SHILAP Revista de lepidopterología. 6. 1347364–1347364. 2 indexed citations

Bierut, Laura J., Tabitha Hendershot, Neal L. Benowitz, et al.. (2023). Smoking cessation, harm reduction, and biomarkers protocols in the PhenX Toolkit: Tools for standardized data collection. SHILAP Revista de lepidopterología. 7. 100081–100081. 1 indexed citations

Patlewicz, Grace, Mark Nelms, & Diego Rua. (2022). Evaluating the utility of the Threshold of Toxicological Concern (TTC) and its exclusions in the biocompatibility assessment of extractable chemical substances from medical devices. Computational Toxicology. 24. 100246–100246. 4 indexed citations

Pan, Huaqin, Stephen W. Edwards, Mark Nelms, et al.. (2022). Linking complex disease and exposure data—insights from an environmental and occupational health study. Journal of Exposure Science & Environmental Epidemiology. 33(1). 12–16. 3 indexed citations

Nelms, Mark, Agnes L. Karmaus, & Grace Patlewicz. (2020). An evaluation of the performance of selected (Q)SARs/expert systems for predicting acute oral toxicity. Computational Toxicology. 16. 100135–100135. 13 indexed citations

Nelms, Mark & Grace Patlewicz. (2020). Derivation of New Threshold of Toxicological Concern Values for Exposure via Inhalation for Environmentally-Relevant Chemicals. Frontiers in Toxicology. 2. 580347–580347. 14 indexed citations

Liu, Jie, Beena Vallanat, Carlton P. Jones, et al.. (2020). Identification of novel activators of the metal responsive transcription factor (MTF-1) using a gene expression biomarker in a microarray compendium. Metallomics. 12(9). 1400–1415. 19 indexed citations

Nelms, Mark, Prachi Pradeep, & Grace Patlewicz. (2019). Evaluating potential refinements to existing Threshold of Toxicological Concern (TTC) values for environmentally-relevant compounds. Regulatory Toxicology and Pharmacology. 109. 104505–104505. 16 indexed citations

10.

Leonard, Jeremy A., Mark Nelms, Evisabel A. Craig, et al.. (2019). A weight of evidence approach to investigate potential common mechanisms in pesticide groups to support cumulative risk assessment: A case study with dinitroaniline pesticides. Regulatory Toxicology and Pharmacology. 107. 104419–104419. 8 indexed citations

11.

Nelms, Mark, Ryan Lougee, David W. Roberts, Ann M. Richard, & Grace Patlewicz. (2019). Comparing and contrasting the coverage of publicly available structural alerts for protein binding. Computational Toxicology. 12. 100100–100100. 3 indexed citations

12.

Nelms, Mark, Claire L. Mellor, Steven J. Enoch, et al.. (2018). A mechanistic framework for integrating chemical structure and high-throughput screening results to improve toxicity predictions. Computational Toxicology. 8. 1–12. 14 indexed citations

13.

Fay, Kellie A., Daniel L. Villeneuve, Joe Swintek, et al.. (2018). Differentiating Pathway-Specific From Nonspecific Effects in High-Throughput Toxicity Data: A Foundation for Prioritizing Adverse Outcome Pathway Development. Toxicological Sciences. 163(2). 500–515. 44 indexed citations

14.

Hill, Thomas, Mark Nelms, Stephen W. Edwards, et al.. (2016). Editor’s Highlight: Negative Predictors of Carcinogenicity for Environmental Chemicals. Toxicological Sciences. 155(1). 157–169. 12 indexed citations

15.

Oki, Noffisat O., Mark Nelms, Shannon Bell, Holly M. Mortensen, & Stephen W. Edwards. (2016). Accelerating Adverse Outcome Pathway Development Using Publicly Available Data Sources. Current Environmental Health Reports. 3(1). 53–63. 51 indexed citations

16.

Nelms, Mark, Gamze Ates, Judith C. Madden, et al.. (2014). Proposal of an in silico profiler for categorisation of repeat dose toxicity data of hair dyes. Archives of Toxicology. 89(5). 733–741. 20 indexed citations

17.

Enoch, Steven J., et al.. (2014). Methods for assigning confidence to toxicity data with multiple values — Identifying experimental outliers. The Science of The Total Environment. 482-483. 358–365. 14 indexed citations

18.

Madden, Judith C., Mark Nelms, M Cronin, & Steven J. Enoch. (2014). Identification of structural alerts for mitochondrial toxicity using chemotyper. Toxicology Letters. 229. S162–S162. 1 indexed citations

19.

Nelms, Mark, M Cronin, T.W. Schultz, & Steven J. Enoch. (2013). Experimental verification, and domain definition, of structural alerts for protein binding: epoxides, lactones, nitroso, nitros, aldehydes and ketones. SAR and QSAR in environmental research. 24(9). 695–709. 9 indexed citations

20.

Cook, J P, et al.. (2004). Modeling and Analysis of Cycloconverter Operation.

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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