Prediction-inspired intelligent training for the development of classification read-across structure–activity relationship (c-RASAR) models for organic skin sensitizers …
A Banerjee, K Roy - Chemical Research in Toxicology, 2023 - ACS Publications
The advancements in the field of cheminformatics have led to a reduction in animal testing to
estimate the activity, property, and toxicity of query chemicals. Read-across structure–activity …
estimate the activity, property, and toxicity of query chemicals. Read-across structure–activity …
Machine learning-based q-RASAR modeling to predict acute contact toxicity of binary organic pesticide mixtures in honey bees
We have reported here a quantitative read-across structure-activity relationship (q-RASAR)
model for the prediction of binary mixture toxicity (acute contact toxicity) in honey bees. Both …
model for the prediction of binary mixture toxicity (acute contact toxicity) in honey bees. Both …
Machine-learning-based similarity meets traditional QSAR:“q-RASAR” for the enhancement of the external predictivity and detection of prediction confidence outliers …
A Banerjee, K Roy - Chemometrics and Intelligent Laboratory Systems, 2023 - Elsevier
Recently, the concept of quantitative Read-Across Structure-Activity Relationship (q-RASAR)
has been introduced by using various Machine Learning (ML)-derived similarity functions in …
has been introduced by using various Machine Learning (ML)-derived similarity functions in …
Efficient predictions of cytotoxicity of TiO2-based multi-component nanoparticles using a machine learning-based q-RASAR approach
The availability of experimental nanotoxicity data is in general limited which warrants both
the use of in silico methods for data gap filling and exploring novel methods for effective …
the use of in silico methods for data gap filling and exploring novel methods for effective …
Read-across-based intelligent learning: development of a global q-RASAR model for the efficient quantitative predictions of skin sensitization potential of diverse …
A Banerjee, K Roy - Environmental Science: Processes & Impacts, 2023 - pubs.rsc.org
Environmental chemicals and contaminants cause a wide array of harmful implications to
terrestrial and aquatic life which ranges from skin sensitization to acute oral toxicity. The …
terrestrial and aquatic life which ranges from skin sensitization to acute oral toxicity. The …
Predictive Quantitative Read-Across Structure–Property Relationship Modeling of the Retention Time (Log tR) of Pesticide Residues Present in Foods and …
S Ghosh, M Chatterjee, K Roy - Journal of Agricultural and Food …, 2023 - ACS Publications
The retention time (log t R) of pesticidal compounds in a reverse-phase high-performance
liquid chromatography (HPLC) analysis has a direct relationship with lipophilicity, which …
liquid chromatography (HPLC) analysis has a direct relationship with lipophilicity, which …
Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease
In the present research, we present the application of a novel approach, termed the Machine
Learning (ML)-Based q-RASAR (quantitative read-across structure-activity relationship) …
Learning (ML)-Based q-RASAR (quantitative read-across structure-activity relationship) …
How to correctly develop q-RASAR models for predictive cheminformatics
A Banerjee, K Roy - Expert Opinion on Drug Discovery, 2024 - Taylor & Francis
One of the earliest and simplest forms of in silico predictive cheminformatics is the
Quantitative Structure-Activity Relationship (QSAR). This algorithm aims to develop a …
Quantitative Structure-Activity Relationship (QSAR). This algorithm aims to develop a …
Ensemble quantitative read-across structure–activity relationship algorithm for predicting skin cytotoxicity
T Srisongkram - Chemical Research in Toxicology, 2023 - ACS Publications
Read-across (RA) and quantitative structure–activity relationship (QSAR) are two alternative
methods commonly used to fill data gaps in chemical registrations. These approaches use …
methods commonly used to fill data gaps in chemical registrations. These approaches use …
Machine learning-based approach for efficient prediction of toxicity of chemical gases using feature selection
Toxic gases can be fatal as they damage many living tissues, especially the nervous and
respiratory systems. They can cause permanent damage for many years by harming …
respiratory systems. They can cause permanent damage for many years by harming …