Development of a robust Machine learning model for Ames test outcome prediction

GS Borah, S Nagamani - Chemical Physics Letters, 2024 - Elsevier
The mutagenicity is an essential parameter for evaluating the safety of pharmaceuticals,
chemicals, consumer products, environmentally related compounds and the Ames assay is …

GeoScatt-GNN: A Geometric Scattering Transform-Based Graph Neural Network Model for Ames Mutagenicity Prediction

A Zoubir, B Missaoui - arxiv preprint arxiv:2411.15331, 2024 - arxiv.org
This paper tackles the pressing challenge of mutagenicity prediction by introducing three
ground-breaking approaches. First, it showcases the superior performance of 2D scattering …

Comparative Evaluation and Data Analysis for Drug Toxicity Prediction

JW Chu, YR Cho - 2024 IEEE International Conference on …, 2024 - ieeexplore.ieee.org
Throughout the entire drug development process, toxicity prediction is a significant process
in assessing the possible toxicity of drugs. Recently, there has been active research on …

Amesformer: a graph transformer neural network for mutagenicity prediction

L Thompson, J Evans, S Matthews - 2024 - chemrxiv.org
The Ames mutagenicity test is a gold standard assay for the safety assessment of new
chemicals. However, many in silico models rely on challenging-to-interpret ensemble …

Amesformer: State-of-the-Art Mutagenicity Prediction with Graph Transformers

L Thompson, J Evans, S Matthews - 2024 - chemrxiv.org
The Ames mutagenicity test is a gold standard assay for the safety assessment of new
chemicals. However, many in silico models rely on challenging-to-interpret ensemble …