Kunal Roy

19.5k total citations · 9 hit papers
464 papers, 14.6k citations indexed

About

Kunal Roy is a scholar working on Computational Theory and Mathematics, Organic Chemistry and Molecular Biology. According to data from OpenAlex, Kunal Roy has authored 464 papers receiving a total of 14.6k indexed citations (citations by other indexed papers that have themselves been cited), including 327 papers in Computational Theory and Mathematics, 101 papers in Organic Chemistry and 90 papers in Molecular Biology. Recurrent topics in Kunal Roy's work include Computational Drug Discovery Methods (327 papers), Free Radicals and Antioxidants (50 papers) and Synthesis and biological activity (43 papers). Kunal Roy is often cited by papers focused on Computational Drug Discovery Methods (327 papers), Free Radicals and Antioxidants (50 papers) and Synthesis and biological activity (43 papers). Kunal Roy collaborates with scholars based in India, United States and Italy. Kunal Roy's co-authors include Supratik Kar, Rudra Narayan Das, Partha Pratim Roy, Indrani Mitra, Pravin Ambure, Probir Kumar Ojha, J. Thomas Leonard, Rahul Balasaheb Aher, Arkaprava Banerjee and Jerzy Leszczyński and has published in prestigious journals such as Chemical Reviews, SHILAP Revista de lepidopterología and Environmental Science & Technology.

In The Last Decade

Kunal Roy

444 papers receiving 14.3k citations

Hit Papers

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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.

On Some Aspects of Variable Selection for Partial Least Squares Regression Models

2007 709 citations Partha Pratim Roy, Kunal Roy QSAR & Combinatorial Science profile →
On a simple approach for determining applicability domain of QSAR models

2015 606 citations Kunal Roy, Supratik Kar et al. Chemometrics and Intelligent Laboratory Systems profile →
Be aware of error measures. Further studies on validation of predictive QSAR models

2016 583 citations Kunal Roy, Rudra Narayan Das et al. Chemometrics and Intelligent Laboratory Systems profile →
Further exploring r metrics for validation of QSPR models

2011 487 citations Probir Kumar Ojha, Rudra Narayan Das et al. Chemometrics and Intelligent Laboratory Systems profile →
On Two Novel Parameters for Validation of Predictive QSAR Models

2009 472 citations Partha Pratim Roy, Kunal Roy et al. profile →
Comparative Studies on Some Metrics for External Validation of QSPR Models

2011 393 citations Kunal Roy, Supratik Kar et al. profile →
Green Chemistry in the Synthesis of Pharmaceuticals

2021 326 citations Supratik Kar, Kunal Roy et al. profile →
Prediction reliability of QSAR models: an overview of various validation tools

2022 115 citations Supratik Kar, Kunal Roy et al. profile →
ARKA: a framework of dimensionality reduction for machine-learning classification modeling, risk assessment, and data gap-filling of sparse environmental toxicity data

2024 40 citations Arkaprava Banerjee, Kunal Roy profile →

Author Peers

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

Author						Papers	Cites
Kunal Roy	8.9k	3.9k	3.7k	1.8k	1.4k	464	14.6k
Roberto Todeschini	8.0k 0.9×	3.4k 0.9×	3.9k 1.1×	1.9k 1.1×	2.2k 1.6×	185	14.1k
Paola Gramatica	8.4k 0.9×	3.6k 0.9×	3.7k 1.0×	2.0k 1.1×	1.8k 1.3×	160	15.5k
Viviana Consonni	6.4k 0.7×	2.4k 0.6×	3.1k 0.8×	1.5k 0.9×	1.5k 1.1×	97	10.9k
Alexander Tropsha	13.7k 1.5×	4.7k 1.2×	9.5k 2.5×	4.5k 2.5×	2.1k 1.5×	307	23.8k
M Cronin	7.4k 0.8×	3.6k 0.9×	8.4k 2.2×	2.5k 1.4×	1.7k 1.2×	359	30.4k
Emilio Benfenati	5.0k 0.6×	1.5k 0.4×	2.2k 0.6×	1.3k 0.7×	1.1k 0.8×	511	11.5k
Igor V. Tetko	5.0k 0.6×	2.0k 0.5×	4.0k 1.1×	2.2k 1.2×	1.6k 1.2×	191	11.5k
Andrey A. Toropov	5.1k 0.6×	1.9k 0.5×	1.6k 0.4×	1.8k 1.0×	896 0.6×	395	7.1k
Evan Bolton	5.1k 0.6×	1.1k 0.3×	7.3k 2.0×	1.6k 0.9×	892 0.6×	71	14.6k

Countries citing papers authored by Kunal Roy

Since Specialization

Citations

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

Fields of papers citing papers by Kunal Roy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kunal Roy

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

Roy, Kunal, et al.. (2025). Predictive classification-based read-across for diverse functional vitiligo-linked chemical exposomes (ViCE): A new approach for the assessment of chemical safety for the vitiligo disease in humans. Toxicology in Vitro. 104. 106018–106018.

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).

Chatterjee, Mainak, et al.. (2024). Machine learning-based q-RASAR predictions of the bioconcentration factor of organic molecules estimated following the organisation for economic co-operation and development guideline 305. Journal of Hazardous Materials. 479. 135725–135725. 9 indexed citations

Chatterjee, Mainak, et al.. (2024). Intelligent consensus-based predictions of early life stage toxicity in fish tested in compliance with OECD Test Guideline 210. Aquatic Toxicology. 279. 107216–107216.

Roy, Kunal, et al.. (2024). Quantitative read-across structure-activity relationship (q-RASAR): A novel approach to estimate the subchronic oral safety (NOAEL) of diverse organic chemicals in rats. Toxicology. 505. 153824–153824. 5 indexed citations

Roy, Kunal, et al.. (2024). First report on regression-based QSAR addressing pesticide dissipation half-life in plants: A step towards sustainable public health. The Science of The Total Environment. 954. 176175–176175. 2 indexed citations

Roy, Kunal, et al.. (2024). Development of hybrid models by the integration of the read-across hypothesis with the QSAR framework for the assessment of developmental and reproductive toxicity (DART) tested according to OECD TG 414. Toxicology Reports. 13. 101822–101822. 3 indexed citations

Roy, Kunal, et al.. (2024). Predictive cheminformatics modeling of reorganization energy (RE) for p-type organic semiconductors: Integration of quantitative read-across structure-property relationship (q-RASPR) and stacking regression analysis. Materials Today Communications. 41. 110430–110430.

Ojha, Probir Kumar, et al.. (2024). Safer and greener chemicals for the aquatic ecosystem: Chemometric modeling of the prolonged and chronic aquatic toxicity of chemicals on Oryzias latipes. Aquatic Toxicology. 273. 106985–106985. 5 indexed citations

10.

Roy, Kunal, et al.. (2024). Insights into nanoparticle toxicity against aquatic organisms using multivariate regression, read-across, and ML algorithms: Predictive models for Daphnia magna and Danio rerio. Aquatic Toxicology. 276. 107114–107114. 2 indexed citations

11.

Banerjee, Arkaprava, et al.. (2024). QSPR and q-RASPR predictions of the adsorption capacity of polyethylene, polypropylene and polystyrene microplastics for various organic pollutants in diverse aqueous environments. Environmental Science Nano. 11(10). 4196–4210. 4 indexed citations

12.

Ojha, Probir Kumar, et al.. (2023). Computational modeling of aquatic toxicity of polychlorinated naphthalenes (PCNs) employing 2D-QSAR and chemical read-across. Aquatic Toxicology. 257. 106429–106429. 12 indexed citations

13.

Roy, Kunal, et al.. (2023). Prediction of cytotoxicity of heavy metals adsorbed on nano-TiO₂ with periodic table descriptors using machine learning approaches. Beilstein Journal of Nanotechnology. 14. 939–950. 3 indexed citations

14.

Banerjee, Arkaprava & Kunal Roy. (2023). Machine-learning-based similarity meets traditional QSAR: “q-RASAR” for the enhancement of the external predictivity and detection of prediction confidence outliers in an hERG toxicity dataset. Chemometrics and Intelligent Laboratory Systems. 237. 104829–104829. 28 indexed citations

15.

Khan, Kabiruddin, Supratik Kar, & Kunal Roy. (2023). Are we ready to combat the ecotoxicity of COVID-19 pharmaceuticals? An in silico aquatic risk assessment. Aquatic Toxicology. 256. 106416–106416. 10 indexed citations

16.

Kumar, Vinay, Arkaprava Banerjee, & Kunal Roy. (2023). Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease. Chemometrics and Intelligent Laboratory Systems. 245. 105049–105049. 18 indexed citations

17.

Chatterjee, Mainak, et al.. (2023). Quantitative Read-across structure-activity relationship (q-RASAR): A new approach methodology to model aquatic toxicity of organic pesticides against different fish species. Aquatic Toxicology. 265. 106776–106776. 10 indexed citations

18.

Roy, Kunal, et al.. (2023). Development of a read-across-derived classification model for the predictions of mutagenicity data and its comparison with traditional QSAR models and expert systems. Toxicology. 500. 153676–153676. 13 indexed citations

19.

Das, Rudra Narayan, Tânia E. Sintra, João A. P. Coutinho, et al.. (2016). Development of predictive QSAR models for Vibrio fischeri toxicity of ionic liquids and their true external and experimental validation tests. Toxicology Research. 5(5). 1388–1399. 27 indexed citations

20.

Roy, Partha Pratim & Kunal Roy. (2007). On Some Aspects of Variable Selection for Partial Least Squares Regression Models. QSAR & Combinatorial Science. 27(3). 302–313. 709 indexed citations breakdown →

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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