Kunal Roy
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View article: Leveraging Convolutional and Transformer Synergy for Robust Camera Source Attribution
Leveraging Convolutional and Transformer Synergy for Robust Camera Source Attribution Open
The majority of contemporary communication relies on electronic devices. Digital images and videos are regarded the primary modes of modern communication.Identifying the source camera model is crucial in digital forensics, having applicati…
View article: Machine Learning (ML)-driven quantitative structure-pharmacokinetic relationship (QSPKR) modeling of the tissue-to-plasma partition coefficient (Kp) of drugs across different tissues
Machine Learning (ML)-driven quantitative structure-pharmacokinetic relationship (QSPKR) modeling of the tissue-to-plasma partition coefficient (Kp) of drugs across different tissues Open
In drug discovery, estimating the drug candidate's pharmacokinetic (PK) parameters is crucial for determining its safety and efficacy within the body. The tissue-to-plasma partition coefficient (Kp) indicates how a drug partitions within a…
View article: AI and ML for small molecule drug discovery in the big data era III
AI and ML for small molecule drug discovery in the big data era III Open
View article: A New Approach Methodology (NAM) for carcinogenicity prediction of organic chemicals using the Multiclass ARKA framework and machine-learning-based stacking regression
A New Approach Methodology (NAM) for carcinogenicity prediction of organic chemicals using the Multiclass ARKA framework and machine-learning-based stacking regression Open
The continuous accumulation of agricultural and industrial chemicals in the environment has significantly impacted the flora and fauna, resulting in disruptions in food chains and disturbances in the biological ecosystem. A high fraction o…
View article: Innovative Sudoku Designs with Rectangular Sub-zones: Enhancing Experimental Precision in Paddy Field Trials
Innovative Sudoku Designs with Rectangular Sub-zones: Enhancing Experimental Precision in Paddy Field Trials Open
This study investigates the application of a Sudoku square design with rectangular subzones for a field experiment on paddy cultivation conducted in 2022-2023 in West Bengal, India. Traditional row column experimental designs, such as the …
View article: The multiclass ARKA framework for developing improved quantitative RASAR models
The multiclass ARKA framework for developing improved quantitative RASAR models Open
Over the last decade, the field of Cheminformatics has witnessed a significant advancement in developing more robust and predictive quantitative structure-activity relationship (QSAR) models. Recently, the quantitative Read-Across Structur…
View article: The q-RASPR approach for predicting the property and fate of persistent organic pollutants
The q-RASPR approach for predicting the property and fate of persistent organic pollutants Open
This study presents a quantitative read-across structure-property relationship (q-RASPR) approach that integrates the chemical similarity information used in read-across with traditional quantitative structure-property relationship (QSPR) …
View article: Machine learning assisted classification RASAR modeling for the nephrotoxicity potential of a curated set of orally active drugs
Machine learning assisted classification RASAR modeling for the nephrotoxicity potential of a curated set of orally active drugs Open
View article: A q-RASAR approach for oral and inhalational toxicity prediction of perfluorinated and polyfluorinated compounds (PFCs) using rodent toxicity data
A q-RASAR approach for oral and inhalational toxicity prediction of perfluorinated and polyfluorinated compounds (PFCs) using rodent toxicity data Open
View article: “intelligent Read Across (iRA)”- A tool for read-across-based toxicity prediction of nanoparticles
“intelligent Read Across (iRA)”- A tool for read-across-based toxicity prediction of nanoparticles Open
View article: Exploration of read-across-based predictions for unveiling the risk of FDA-labeled drug-induced cardiotoxicity (DICT) rank: A careful classification of the most extensive reference list of human drugs
Exploration of read-across-based predictions for unveiling the risk of FDA-labeled drug-induced cardiotoxicity (DICT) rank: A careful classification of the most extensive reference list of human drugs Open
View article: The round-robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential
The round-robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential Open
A key step in building regulatory acceptance of alternative or non-animal test methods has long been the use of interlaboratory comparisons or round-robins (RRs), in which a common test material and standard operating procedure is provided…
View article: 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
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 Open
View article: Organic Sunscreens and Their Products of Degradation in Biotic and Abiotic Conditions—In Silico Studies of Drug-Likeness and Human Placental Transport
Organic Sunscreens and Their Products of Degradation in Biotic and Abiotic Conditions—In Silico Studies of Drug-Likeness and Human Placental Transport Open
A total of 16 organic sunscreens and over 160 products of their degradation in biotic and abiotic conditions were investigated in the context of their safety during pregnancy. Drug-likeness and the ability of the studied compounds to be ab…
View article: The application of chemical similarity measures in an unconventional modeling framework c-RASAR along with dimensionality reduction techniques to a representative hepatotoxicity dataset
The application of chemical similarity measures in an unconventional modeling framework c-RASAR along with dimensionality reduction techniques to a representative hepatotoxicity dataset Open
View article: Machine learning-assisted c-RASAR modeling of a curated set of orally active nephrotoxic drugs: Similarity-based predictions from close source neighbors
Machine learning-assisted c-RASAR modeling of a curated set of orally active nephrotoxic drugs: Similarity-based predictions from close source neighbors Open
Cheminformatics and Machine Learning (ML) have seen exponential progress in the last decade, in the field of chemical risk assessment, due to their efficiency, accuracy, and reliability. The constant evolution of New Approach Methodologies…
View article: The Round Robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential
The Round Robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential Open
A key step in building regulatory acceptance of alternative or non-animal test methods has long been the use of interlaboratory comparisons or Round Robins (RR), in which a common test material and standard operating procedure is provided …
View article: Driving factors for developing integrated farming: Multi-criteria decision-making analysis
Driving factors for developing integrated farming: Multi-criteria decision-making analysis Open
Integrated farming (IF) by temporal and spatial mixing of crops, livestock, fishery, and allied activities in a single farm, is considered a critical multifunctional option for smallholder farmers, who form the backbone of Indian agricultu…
View article: Cover Image
Cover Image Open
Chemical Biology & Drug Design is a peer-reviewed scientific journal that is dedicated to the advancement of innovative science, technology and medicine with a focus on the multidisciplinary fields of chemical biology and drug design.It is…
View article: Cover Image
Cover Image Open
Chemical Biology & Drug Design is a peer-reviewed scientific journal that is dedicated to the advancement of innovative science, technology and medicine with a focus on the multidisciplinary fields of chemical biology and drug design.It is…
View article: ARKA: A framework of dimensionality reduction for machine-learning classification modeling, risk assessment, and data gap-filling of sparse environmental toxicity data
ARKA: A framework of dimensionality reduction for machine-learning classification modeling, risk assessment, and data gap-filling of sparse environmental toxicity data Open
Toxicity assessment of environmental chemicals is an integral aspect of assessing the sustainability of flora and fauna constituting the aquatic and terrestrial ecosystems. A wide variety of living organisms are constantly being exposed to…
View article: A Personalized Video Recommendation Model Based on Multi-Graph Neural Network and Attention Mechanism
A Personalized Video Recommendation Model Based on Multi-Graph Neural Network and Attention Mechanism Open
The sheer volume of available data makes it challenging for users to sift through and find the information they truly need. Recommender systems play a pivotal role in addressing this challenge by leveraging users' historical interaction da…
View article: Exploring the relationships between physiochemical properties of nanoparticles and cell damage to combat cancer growth using simple periodic table-based descriptors
Exploring the relationships between physiochemical properties of nanoparticles and cell damage to combat cancer growth using simple periodic table-based descriptors Open
A comprehensive knowledge of the physical and chemical properties of nanomaterials (NMs) is necessary to design them effectively for regulated use. Although NMs are utilized in therapeutics, their cytotoxicity has attracted great attention…
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Cover Image Open
Chemical Biology & Drug Design is a peer-reviewed scientific journal that is dedicated to the advancement of innovative science, technology and medicine with a focus on the multidisciplinary fields of chemical biology and drug design.It is…
View article: Insights into pharmacokinetic properties for exposure chemicals: predictive modelling of human plasma fraction unbound (<i>f</i><sub>u</sub>) and hepatocyte intrinsic clearance (Cl<sub>int</sub>) data using machine learning
Insights into pharmacokinetic properties for exposure chemicals: predictive modelling of human plasma fraction unbound (<i>f</i><sub>u</sub>) and hepatocyte intrinsic clearance (Cl<sub>int</sub>) data using machine learning Open
We have developed regression-based models with the protein fraction unbound ( f u ) human data set and a classification-based model with the hepatocyte intrinsic clearance (Cl int ) human data set collected from the recently published ICE …
View article: Predicting the performance and stability parameters of energetic materials (EMs) using a machine learning-based q-RASPR approach
Predicting the performance and stability parameters of energetic materials (EMs) using a machine learning-based q-RASPR approach Open
ML-based q-RASPR provides better predictions than QSPR for the performance and stability parameters of energetic materials (EMs).
View article: Chemometric modeling of the lowest observed effect level (LOEL) and no observed effect level (NOEL) for rat toxicity
Chemometric modeling of the lowest observed effect level (LOEL) and no observed effect level (NOEL) for rat toxicity Open
Humans and other living species of the ecosystem are constantly exposed to a wide range of chemicals of natural as well as synthetic origin.
View article: Cover Image
Cover Image Open
Chemical Biology & Drug Design is a peer-reviewed scientific journal that is dedicated to the advancement of innovative science, technology and medicine with a focus on the multidisciplinary fields of chemical biology and drug design.It is…
View article: Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease
Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease Open
In the present research, we propose a novel approach, termed the Machine Learning (ML)-Based q-RASAR (quantitative read-across structure-activity relationship) method, for the identification of potential multi-target inhibitors against AD.…
View article: Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease
Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease Open
In the present research, we propose a novel approach, termed the Machine Learning (ML)-Based q-RASAR (quantitative read-across structure-activity relationship) method, for the identification of potential multi-target inhibitors against AD.…