Emilio Benfenati

19.9k total citations · 1 hit paper
511 papers, 11.5k citations indexed

About

Emilio Benfenati is a scholar working on Computational Theory and Mathematics, Health, Toxicology and Mutagenesis and Molecular Biology. According to data from OpenAlex, Emilio Benfenati has authored 511 papers receiving a total of 11.5k indexed citations (citations by other indexed papers that have themselves been cited), including 290 papers in Computational Theory and Mathematics, 133 papers in Health, Toxicology and Mutagenesis and 85 papers in Molecular Biology. Recurrent topics in Emilio Benfenati's work include Computational Drug Discovery Methods (290 papers), Analytical Chemistry and Chromatography (77 papers) and Pesticide Residue Analysis and Safety (62 papers). Emilio Benfenati is often cited by papers focused on Computational Drug Discovery Methods (290 papers), Analytical Chemistry and Chromatography (77 papers) and Pesticide Residue Analysis and Safety (62 papers). Emilio Benfenati collaborates with scholars based in Italy, United States and Germany. Emilio Benfenati's co-authors include Andrey A. Toropov, Alla P. Toropova, Giuseppina Gini, Alessandra Roncaglioni, Jerzy Leszczyński, Anna Lombardo, Alberto Manganaro, Kunal Roy, Roberto Fanelli and Danuta Leszczyńska and has published in prestigious journals such as Chemical Reviews, Chemical Society Reviews and SHILAP Revista de lepidopterología.

In The Last Decade

Emilio Benfenati

506 papers receiving 11.2k citations

Hit Papers

align trajectories sort by overperformance

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.

Green Chemistry in the Synthesis of Pharmaceuticals

2021 326 citations Supratik Kar, Kunal Roy et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Emilio Benfenati	5.0k	3.2k	2.2k	1.8k	1.5k	511	11.5k
Paola Gramatica	8.4k 1.7×	2.7k 0.8×	3.7k 1.7×	2.0k 1.1×	3.6k 2.4×	160	15.5k
Gerrit Schüürmann	2.1k 0.4×	3.4k 1.1×	2.3k 1.1×	2.5k 1.4×	4.3k 2.9×	247	16.6k
T.W. Schultz	2.8k 0.6×	2.6k 0.8×	1.5k 0.7×	1.4k 0.8×	1.2k 0.8×	231	7.5k
Kunal Roy	8.9k 1.8×	1.4k 0.4×	3.7k 1.7×	909 0.5×	3.9k 2.6×	464	14.6k
Andrew Worth	2.9k 0.6×	2.3k 0.7×	1.4k 0.6×	768 0.4×	792 0.5×	198	8.1k
Ann M. Richard	3.9k 0.8×	4.1k 1.3×	2.9k 1.3×	938 0.5×	498 0.3×	116	10.2k
M Cronin	7.4k 1.5×	5.6k 1.8×	8.4k 3.9×	1.8k 1.0×	3.6k 2.4×	359	30.4k
Roberto Todeschini	8.0k 1.6×	972 0.3×	3.9k 1.8×	584 0.3×	3.4k 2.3×	185	14.1k
Viviana Consonni	6.4k 1.3×	710 0.2×	3.1k 1.5×	436 0.2×	2.4k 1.6×	97	10.9k
Joop L. M. Hermens	1.6k 0.3×	7.5k 2.3×	975 0.5×	4.8k 2.6×	741 0.5×	234	12.0k

Countries citing papers authored by Emilio Benfenati

Since Specialization

Citations

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

Fields of papers citing papers by Emilio Benfenati

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emilio Benfenati

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

Roncaglioni, Alessandra, et al.. (2025). Predicting Acute Oral Toxicity in Bobwhite Quail: Development of QSAR Models for LD50. Environments. 12(2). 56–56. 1 indexed citations

Roncaglioni, Alessandra, et al.. (2025). The evolution of the EFSA OpenFoodTox database. 3(1). 1798–1798. 1 indexed citations

Banerjee, Arkaprava, Supratik Kar, Kunal Roy, et al.. (2025). From Feature‐Based Chemical Similarity to Chemical Language Models—A Paradigm Shift in Computer‐Aided Molecular Design and Property Predictions. Wiley Interdisciplinary Reviews Computational Molecular Science. 15(6).

Gadaleta, Domenico, et al.. (2024). Comprehensive benchmarking of computational tools for predicting toxicokinetic and physicochemical properties of chemicals. Journal of Cheminformatics. 16(1). 145–145. 2 indexed citations

Benfenati, Emilio, Franca M. Buratti, Chiara Dall’Asta, et al.. (2024). Generic kinetic and kinetic‐dynamic modelling in human subgroups of the population and animal species to support transparency in food and feed safety: Case studies. EFSA Supporting Publications. 21(12). 1 indexed citations

Luciani, Davide, et al.. (2024). ToxEraser cosmetics: A new tool for substitution, towards safer cosmetic ingredients. Computational Toxicology. 31. 100323–100323. 1 indexed citations

Topping, Christopher John, Agnieszka J. Bednarska, Emilio Benfenati, et al.. (2024). PollinERA: Understanding pesticide-Pollinator interactions to support EU Environmental Risk Assessment and policy. SHILAP Revista de lepidopterología. 10. 2 indexed citations

Gadaleta, Domenico, et al.. (2023). A KNIME Workflow to Assist the Analogue Identification for Read-Across, Applied to Aromatase Activity. Molecules. 28(4). 1832–1832. 8 indexed citations

Chatterjee, Mainak, Arkaprava Banerjee, Simone Tosi, et al.. (2023). Machine learning - based q-RASAR modeling to predict acute contact toxicity of binary organic pesticide mixtures in honey bees. Journal of Hazardous Materials. 460. 132358–132358. 29 indexed citations

10.

Toropova, Alla P., Andrey A. Toropov, Alessandra Roncaglioni, & Emilio Benfenati. (2023). Using the Correlation Intensity Index to Build a Model of Cardiotoxicity of Piperidine Derivatives. Molecules. 28(18). 6587–6587. 3 indexed citations

11.

Luconi, Michaela, Miguel Á. Sogorb, Udo R. Markert, et al.. (2022). Human-Based New Approach Methodologies in Developmental Toxicity Testing: A Step Ahead from the State of the Art with a Feto–Placental Organ-on-Chip Platform. International Journal of Environmental Research and Public Health. 19(23). 15828–15828. 11 indexed citations

12.

Tan, Haoyue, Qinchang Chen, Huixiao Hong, et al.. (2021). Structures of Endocrine-Disrupting Chemicals Correlate with the Activation of 12 Classic Nuclear Receptors. Environmental Science & Technology. 55(24). 16552–16562. 38 indexed citations

13.

Fernández‐Cruz, María Luisa, et al.. (2020). Comparing in vivo data and in silico predictions for acute effects assessment of biocidal active substances and metabolites for aquatic organisms. Ecotoxicology and Environmental Safety. 205. 111291–111291. 5 indexed citations

14.

Tan, Haoyue, Xiaoxiang Wang, Huixiao Hong, et al.. (2020). Structures of Endocrine-Disrupting Chemicals Determine Binding to and Activation of the Estrogen Receptor α and Androgen Receptor. Environmental Science & Technology. 54(18). 11424–11433. 63 indexed citations

15.

Khan, Kabiruddin, Giovanna J. Lavado, Diego Baderna, et al.. (2019). QSAR modeling of Daphnia magna and fish toxicities of biocides using 2D descriptors. Chemosphere. 229. 8–17. 77 indexed citations

16.

Raitano, Giuseppa, Daniele Goi, Valentina Pieri, et al.. (2018). (Eco)toxicological maps: A new risk assessment method integrating traditional and in silico tools and its application in the Ledra River (Italy). Environment International. 119. 275–286. 12 indexed citations

17.

Toropova, Alla P., Andrey A. Toropov, Jovana B. Veselinović, et al.. (2015). Application of the Monte Carlo Method to prediction of Dispersibility of Graphene in Various Solvents. International Journal of Environmental Research. 9(4). 1211–1216. 2 indexed citations

18.

Lombardo, Anna, et al.. (2014). A new in silico classification model for ready biodegradability, based on molecular fragments. Chemosphere. 108. 10–16. 34 indexed citations

19.

Fratev, F., et al.. (2007). Study of species-specific carcinogenicity of benzene derivatives. 1. Combination of CoMFA and GRID analysis. 30(4). 891–911. 1 indexed citations

20.

Benfenati, Emilio, et al.. (2002). Neuro-fuzzy knowledge representation for toxicity prediction of organic compounds. European Conference on Artificial Intelligence. 498–502. 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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