Antonio Cassano

2.0k total citations
9 papers, 408 citations indexed

About

Antonio Cassano is a scholar working on Health, Toxicology and Mutagenesis, Computational Theory and Mathematics and Environmental Chemistry. According to data from OpenAlex, Antonio Cassano has authored 9 papers receiving a total of 408 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Health, Toxicology and Mutagenesis, 5 papers in Computational Theory and Mathematics and 2 papers in Environmental Chemistry. Recurrent topics in Antonio Cassano's work include Computational Drug Discovery Methods (5 papers), Environmental Toxicology and Ecotoxicology (5 papers) and Chemistry and Chemical Engineering (2 papers). Antonio Cassano is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Environmental Toxicology and Ecotoxicology (5 papers) and Chemistry and Chemical Engineering (2 papers). Antonio Cassano collaborates with scholars based in Italy, United Kingdom and United States. Antonio Cassano's co-authors include Emilio Benfenati, Richard Marchese Robinson, M Cronin, Jerzy Leszczyński, Bakhtiyor Rasulev, Alberto Manganaro, Douglas Young, Todd M. Martin, Nadège Piclin and Davide Bigoni and has published in prestigious journals such as Nanoscale, Toxicology Letters and Chemistry Central Journal.

In The Last Decade

Antonio Cassano

9 papers receiving 405 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Antonio Cassano Italy	8	149	126	125	70	57	9	408
Serena Manganelli Italy	13	110 0.7×	262 2.1×	87 0.7×	38 0.5×	28 0.5×	27	484
Sandy Weiner United States	6	62 0.4×	92 0.7×	48 0.4×	24 0.3×	38 0.7×	8	299
Natalja Fjodorova Slovenia	10	97 0.7×	240 1.9×	44 0.4×	19 0.3×	39 0.7×	23	379
Diana Montes‐Grajales Colombia	10	45 0.3×	47 0.4×	179 1.4×	170 2.4×	27 0.5×	15	535
Michael Comber United Kingdom	8	25 0.2×	184 1.5×	191 1.5×	115 1.6×	54 0.9×	10	544
Elton Zvinavashe Netherlands	8	25 0.2×	170 1.3×	139 1.1×	42 0.6×	12 0.2×	8	318
Claudia Cappelli Italy	12	32 0.2×	122 1.0×	126 1.0×	80 1.1×	22 0.4×	14	325
Worth Andrew	15	18 0.1×	152 1.2×	183 1.5×	67 1.0×	27 0.5×	36	449
David J. Ponting United Kingdom	16	30 0.2×	86 0.7×	328 2.6×	49 0.7×	79 1.4×	37	740
Giovanna J. Lavado Italy	9	27 0.2×	224 1.8×	101 0.8×	47 0.7×	20 0.4×	17	375

Countries citing papers authored by Antonio Cassano

Since Specialization

Citations

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

Fields of papers citing papers by Antonio Cassano

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Antonio Cassano

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

All Works

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9 of 9 papers shown

Ma, Jin, Lena Nguyen, Antonio Cassano, et al.. (2022). Correlation of respiratory oscillometry with CT image analysis in a prospective cohort of idiopathic pulmonary fibrosis. BMJ Open Respiratory Research. 9(1). e001163–e001163. 12 indexed citations

Lombardo, Anna, et al.. (2019). A New QSAR Model for Acute Fish Toxicity based on Mined Structural Alerts. 5(1). 8 indexed citations

Cassano, Antonio, Richard Marchese Robinson, Anna Palczewska, et al.. (2016). Comparing the CORAL and Random Forest Approaches for Modelling the In Vitro Cytotoxicity of Silica Nanomaterials. Alternatives to Laboratory Animals. 44(6). 533–556. 30 indexed citations

Sizochenko, Natalia, Bakhtiyor Rasulev, Antonio Cassano, et al.. (2016). Classification nano-SAR modeling of metal oxides nanoparticles genotoxicity based on comet assay data. Toxicology Letters. 258. S271–S271. 2 indexed citations

Cappelli, Claudia, et al.. (2015). Assessment ofin silicomodels for acute aquatic toxicity towards fish under REACH regulation. SAR and QSAR in environmental research. 26(12). 977–999. 17 indexed citations

Rasulev, Bakhtiyor, Antonio Cassano, Richard Marchese Robinson, et al.. (2014). Genotoxicity of metal oxide nanomaterials: review of recent data and discussion of possible mechanisms. Nanoscale. 7(6). 2154–2198. 151 indexed citations

Cassano, Antonio, Giuseppa Raitano, Enrico Mombelli, et al.. (2014). Evaluation of QSAR Models for the Prediction of Ames Genotoxicity: A Retrospective Exercise on the Chemical Substances Registered Under the EU REACH Regulation. Journal of Environmental Science and Health Part C. 32(3). 273–298. 59 indexed citations

Cassano, Antonio, et al.. (2014). Comparison ofin silicomodels for prediction ofDaphnia magnaacute toxicity. SAR and QSAR in environmental research. 25(8). 673–694. 33 indexed citations

Cassano, Antonio, Alberto Manganaro, Todd M. Martin, et al.. (2010). CAESAR models for developmental toxicity. Chemistry Central Journal. 4(S1). S4–S4. 96 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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