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 …

First report of q-RASAR modeling toward an approach of easy interpretability and efficient transferability

A Banerjee, K Roy - Molecular Diversity, 2022 - Springer
Quantitative structure–activity relationship (QSAR) and read-across techniques have
recently been merged into a new emerging field of read-across structure–activity …

On some novel similarity-based functions used in the ML-based q-RASAR approach for efficient quantitative predictions of selected toxicity end points

A Banerjee, K Roy - Chemical Research in Toxicology, 2023 - ACS Publications
The novel quantitative read-across structure–activity relationship (q-RASAR) approach uses
read-across-derived similarity functions in the quantitative structure–activity relationship …

Molecular similarity in chemical informatics and predictive toxicity modeling: from quantitative read-across (q-RA) to quantitative read-across structure–activity …

A Banerjee, S Kar, K Roy, G Patlewicz… - Critical Reviews in …, 2024 - Taylor & Francis
This article aims to provide a comprehensive critical, yet readable, review of general interest
to the chemistry community on molecular similarity as applied to chemical informatics and …

Quantitative predictions from chemical read-across and their confidence measures

A Banerjee, M Chatterjee, P De, K Roy - Chemometrics and Intelligent …, 2022 - Elsevier
In silico modeling new approach methodologies (NAMs) are viewed as a promising starting
point for filling the existing gaps in safety and ecosafety data. Read-across is one of the most …

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 …

Machine learning-assisted prediction of the biological activity of aromatase inhibitors and data mining to explore similar compounds

M Ishfaq, M Aamir, F Ahmad, AM Mebed… - ACS omega, 2022 - ACS Publications
Designing molecules for drugs has been a hot topic for many decades. However, it is hard
and expensive to find a new molecule. Thus, the cost of the final drug is also increased …

Efficient predictions of cytotoxicity of TiO2-based multi-component nanoparticles using a machine learning-based q-RASAR approach

A Banerjee, S Kar, S Pore, K Roy - Nanotoxicology, 2023 - Taylor & Francis
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 …

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 …

What Structural Biology Tells Us About the Mode of Action and Detection of Toxicants

A le Maire, W Bourguet - Annual Review of Pharmacology and …, 2024 - annualreviews.org
The study of the adverse effects of chemical substances on living organisms is an old and
intense field of research. However, toxicological and environmental health sciences have …