Serena Manganelli

872 total citations
27 papers, 484 citations indexed

About

Serena Manganelli is a scholar working on Computational Theory and Mathematics, Health, Toxicology and Mutagenesis and Environmental Chemistry. According to data from OpenAlex, Serena Manganelli has authored 27 papers receiving a total of 484 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computational Theory and Mathematics, 8 papers in Health, Toxicology and Mutagenesis and 8 papers in Environmental Chemistry. Recurrent topics in Serena Manganelli's work include Computational Drug Discovery Methods (18 papers), Chemistry and Chemical Engineering (8 papers) and Effects and risks of endocrine disrupting chemicals (6 papers). Serena Manganelli is often cited by papers focused on Computational Drug Discovery Methods (18 papers), Chemistry and Chemical Engineering (8 papers) and Effects and risks of endocrine disrupting chemicals (6 papers). Serena Manganelli collaborates with scholars based in Italy, Switzerland and Japan. Serena Manganelli's co-authors include Emilio Benfenati, Alberto Manganaro, Alessandra Roncaglioni, Alessandro Esposito, Domenico Gadaleta, Andrey A. Toropov, Alla P. Toropova, Enrico Mombelli, Cosimo Toma and Masamitsu Honma and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Chemosphere.

In The Last Decade

Serena Manganelli

27 papers receiving 479 citations

Peers

Countries citing papers authored by Serena Manganelli

Since Specialization

Citations

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

Fields of papers citing papers by Serena Manganelli

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Serena Manganelli

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

#	Work	Indexed citations
1	VERMEER FCM: A tool integrating exposure and hazard modelling for chemicals migrating from food contact materials 2024 ·Food and Chemical Toxicology ·Ilse Van Overmeire, (unknown), Philippe Ciffroy, Alberto Manganaro, (unknown), (unknown), Emilio Benfenati, Serena Manganelli, Els Van Hoeck, Birgit Mertens	1
2	In silico approaches in carcinogenicity hazard assessment: case study of pregabalin, a nongenotoxic mouse carcinogen 2023 ·SHILAP Revista de lepidopterología ·Douglas A. Keller, Arianna Bassan, Alexander Amberg, Leigh Ann Burns‐Naas, Jon Chambers, Kevin P. Cross, Frances Hall, Gloria D. Jahnke, (unknown), Serena Manganelli, Jordi Mestres, (unknown), David Woolley, Raymond R. Tice	4
3	Using VEGAHUB Within a Weight-of-Evidence Strategy 2022 ·Methods in molecular biology ·Serena Manganelli, (unknown), (unknown), Emilio Benfenati	4
4	Value and limitation of structure-based profilers to characterize developmental and reproductive toxicity potential 2020 ·Archives of Toxicology ·Serena Manganelli, Benoı̂t Schilter, Gabriele Scholz, Emilio Benfenati, Elena Lo Piparo	5
5	Prediction of the Partition Coefficient between Adipose Tissue and Blood for Environmental Chemicals: From Single QSAR Models to an Integrated Approach 2020 ·Molecular Informatics ·Claudia Cappelli, Serena Manganelli, Cosimo Toma, Emilio Benfenati, Enrico Mombelli	3
6	Development, validation and integration of in silico models to identify androgen active chemicals 2018 ·Chemosphere ·Serena Manganelli, Alessandra Roncaglioni, Kamel Mansouri, Richard Judson, Emilio Benfenati, Alberto Manganaro, Patricia Ruíz	24
7	QSAR Modeling of ToxCast Assays Relevant to the Molecular Initiating Events of AOPs Leading to Hepatic Steatosis 2018 ·Journal of Chemical Information and Modeling ·Domenico Gadaleta, Serena Manganelli, Alessandra Roncaglioni, Cosimo Toma, Emilio Benfenati, Enrico Mombelli	58
8	Development and validation of computational models for predicting oxidative stress responses using comprehensive series of drug-like compounds 2018 ·Toxicology Letters ·Manuel Pastor, Gerard J. P. van Westen, José Carlos Gómez-Tamayo, (unknown), Chi Chung Lam, Bob van de Water, Ulf Norinder, Serena Manganelli, Domenico Gadaleta, Alessandra Roncaglioni	2
9	(Q)SAR tools for priority setting: A case study with printed paper and board food contact material substances 2017 ·Food and Chemical Toxicology ·(unknown), Els Van Hoeck, Giuseppa Raitano, Serena Manganelli, (unknown), Gamze Ates, Tamara Vanhaecke, Sabine Van Miert, Emilio Benfenati, Birgit Mertens, Vera Rogiers	16
10	Nano-QSAR Model for Predicting Cell Viability of Human Embryonic Kidney Cells 2017 ·Methods in molecular biology ·Serena Manganelli, Emilio Benfenati	15
11	Integrated strategy for mutagenicity prediction applied to food contact chemicals 2017 ·ALTEX ·Serena Manganelli	10
12	Integrated strategy for mutagenicity prediction applied to food contact chemicals_suppl2 2017 ·ALTEX ·Serena Manganelli	1
13	Integrating computational methods to predict mutagenicity of aromatic azo compounds 2017 ·Journal of Environmental Science and Health Part C ·Domenico Gadaleta, (unknown), (unknown), Serena Manganelli, Alberto Manganaro, Guido Sello, Masamitsu Honma, Emilio Benfenati	6
14	A knowledge-based expert rule system for predicting mutagenicity (Ames test) of aromatic amines and azo compounds 2016 ·Toxicology ·Domenico Gadaleta, Serena Manganelli, Alberto Manganaro, (unknown), Emilio Benfenati	25
15	New Quantitative Structure–Activity Relationship Models Improve Predictability of Ames Mutagenicity for Aromatic Azo Compounds 2016 ·Toxicological Sciences ·Serena Manganelli, Emilio Benfenati, Alberto Manganaro, Sunil Kulkarni, Tara S. Barton‐Maclaren, Masamitsu Honma	25
16	Use of Read-Across Tools 2016 ·Methods in molecular biology ·Serena Manganelli, Emilio Benfenati	14
17	Comparison ofin silicotools for evaluating rat oral acute toxicity 2015 ·SAR and QSAR in environmental research ·(unknown), Serena Manganelli, Alessandro Esposito, Alessandra Roncaglioni, Alberto Manganaro, Emilio Benfenati	107
18	QSAR model for predicting cell viability of human embryonic kidney cells exposed to SiO2 nanoparticles 2015 ·Chemosphere ·Serena Manganelli, (unknown), Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati	39
19	Hierarchical Rules for Read-Across and In Silico Models of Mutagenicity 2015 ·Journal of Environmental Science and Health Part C ·Emilio Benfenati, Serena Manganelli, Sabrina Giordano, Giuseppa Raitano, Alberto Manganaro	9
20	Validation of quantitative structure–activity relationship models to predict water-solubility of organic compounds 2013 ·The Science of The Total Environment ·Claudia Cappelli, Serena Manganelli, Anna Lombardo, Andrea Gissi, Emilio Benfenati	16

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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