Kunal Roy

Bidhan Chandra Krishi Viswavidyalaya — India

Computer Science · Physical Sciences

62h-index19.3kcitations667works6.22yr avg
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Research Topics

Computational Drug Discovery Methods(425), Free Radicals and Antioxidants(63), Chemistry and Chemical Engineering(56), Analytical Chemistry and Chromatography(55), Metabolomics and Mass Spectrometry Studies(54)

Publications667 total

Machine-learning driven structural space exploration for the characterization of the sweetness and bitterness profile of the most extensive set of organic compounds
Journal of the Indian Chemical Society·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·2025· 3 citedOpen Access
Leveraging Convolutional and Transformer Synergy for Robust Camera Source Attribution
2025Open Access
Assessing biodegradability potential of organic chemicals in aquatic and soil environment through classification-based machine learning models developed in accordance with OECD standards
The Science of The Total Environment·2025· 1 cited
Machine Learning (ML)-driven quantitative structure-pharmacokinetic relationship (QSPKR) modeling of the tissue-to-plasma partition coefficient (Kp) of drugs across different tissues
Artificial Intelligence Chemistry·2025· 1 citedOpen Access
A new approach methodology (NAM) for carcinogenicity prediction of organic chemicals using the multiclass ARKA framework and machine-learning-based stacking regression
Journal of Hazardous Materials·2025· 2 cited
Prediction of bioconcentration factors (BCFs) and bioaccumulation factors (BAFs) for per- and polyfluoroalkyl substances (PFASs) using Read-Across and q-RASPR
The Science of The Total Environment·2025· 2 cited
Machine learning-based q-RASAR modelling for the in silico identification of novel α7nAChR agonists for anti-Alzheimer’s drug discovery
SAR and QSAR in environmental research·2025
Quantitative read-across structure-property relationship (q-RASPR)-based lipid-normalized dietary biomagnification (BMFL) prediction: A framework for evaluating biomagnification potential of organic chemicals in the aquatic ecosystem
Aquatic Toxicology·2025· 1 cited
AI and ML for small molecule drug discovery in the big data era III
Molecular Diversity·2025Open Access
Development of Machine Learning‐Based Models for Mutagenicity Predictions with Applications to Non‐Sugar Sweeteners
Molecular Informatics·2025· 2 cited
Chronic and acute eco-toxicity modeling of carcinogenic and hazardous air pollutants toward humans for critical risk assessment and regulatory decision-making
Computational Toxicology·2025
A New Approach Methodology (NAM) for carcinogenicity prediction of organic chemicals using the Multiclass ARKA framework and machine-learning-based stacking regression
2025· 1 citedOpen Access
QSPR modeling of thermal stability of reactive and self-reactive chemicals using 2D descriptors: Predictions of heat of decomposition, Self-Accelerating decomposition temperature, and onset temperature
Materials Today Communications·2025· 1 cited
Embracing the changes and challenges with modern early drug discovery
Expert Opinion on Drug Discovery·2025· 11 cited
Innovative Sudoku Designs with Rectangular Sub-zones: Enhancing Experimental Precision in Paddy Field Trials
Archives of Current Research International·2025Open Access
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·2025· 3 citedOpen Access
The multiclass ARKA framework for developing improved quantitative RASAR models
2025· 1 citedOpen Access
The q-RASPR approach for predicting the property and fate of persistent organic pollutants
Scientific Reports·2025· 2 citedOpen Access
Machine learning assisted classification RASAR modeling for the nephrotoxicity potential of a curated set of orally active drugs
Scientific Reports·2025· 7 citedOpen Access
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Frequent Co-authors

Supratik Kar(20), Pravin Ambure(10), Rudra Narayan Das(10), Indrani Mitra(9), Probir Kumar Ojha(7), Partha Pratim Roy(6), Emilio Benfenati(5), Jerzy Leszczyński(5), Agnieszka Gajewicz(4), Tomasz Puzyn(4), Rahul Balasaheb Aher(3), J. Thomas Leonard(3), Kabiruddin Khan(3), Hans Sanderson(2), Md. Humayun Kabir(2), Priyanka De(2), Arkaprava Banerjee(2), Pathan Mohsin Khan(2), Somnath Paul(1), Pratim Chakraborty(1)