A deep learning-based quantitative structure-activity relationship analysis, namely the molecular image-based DeepSNAP-deep learning method, can successfully and automatically capture the spatial and temporal features in an image generated from a thr...
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Feb 24, 2023
Calcium-activated chloride channels (CaCCs) are chloride channels that are regulated according to intracellular calcium ion concentrations. The channel protein ANO1 is widely present in cells and is involved in physiological activities including cell...
Prediction of the potency of bioactive compounds generally relies on linear or nonlinear quantitative structure-activity relationship (QSAR) models. Nonlinear models are generated using machine learning methods. We introduce a novel approach for pote...
In this study, the specific surface area of various perovskites was modeled using a novel quantitative read-across structure-property relationship (q-RASPR) approach, which clubs both Read-Across (RA) and quantitative structure-property relationship ...
Machine learning (ML) has become an indispensable tool to predict absorption, distribution, metabolism, and excretion (ADME) properties in pharmaceutical research. ML algorithms are trained on molecular structures and corresponding ADME assay data to...
Journal of chemical information and modeling
Jan 30, 2023
Quantitative structure-property relationships (QSPRs) are important tools to facilitate and accelerate the discovery of compounds with desired properties. While many QSPRs have been developed, they are associated with various shortcomings such as a l...
Journal of chemical information and modeling
Jan 22, 2023
Ionization energy (IE) is an important property of molecules. It is highly desirable to predict IE efficiently based on, for example, machine learning (ML)-powered quantitative structure-property relationships (QSPR). In this study, we systematically...
Efficacy and safety are among the most desirable characteristics of an ideal drug. The tremendous increase in computing power and the entry of artificial intelligence into the field of computational drug design are accelerating the process of identif...
Journal of chemical information and modeling
Dec 15, 2022
Herein, a robust and reproducible eXplainable Artificial Intelligence (XAI) approach is presented, which allows prediction of developmental toxicity, a challenging human-health endpoint in toxicology. The application of XAI as an alternative method i...
Machine learning based statistical models have played a significant role in increasing the speed and accuracy with which the chemical and physical properties of chemical compounds can be predicted as compared to the experimental, and traditional ab i...
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