Ensemble machine learning approach for quantitative structure activity relationship based drug discovery: A Review
This comprehensive review explores the pivotal role of ensemble machine learning
techniques in Quantitative Structure-Activity Relationship (QSAR) modeling for drug …
techniques in Quantitative Structure-Activity Relationship (QSAR) modeling for drug …
A novel hybrid binary whale optimization algorithm with chameleon hunting mechanism for wrapper feature selection in QSAR classification model: A drug-induced …
R Zhou, Y Zhang, K He - Expert Systems with Applications, 2023 - Elsevier
High dimensionality is one of the main challenges in Quantitative Structure-Activity
Relationship (QSAR) classification modeling, and feature selection as an effective …
Relationship (QSAR) classification modeling, and feature selection as an effective …
Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
K Baran, A Kloskowski - The Journal of Physical Chemistry B, 2023 - ACS Publications
Ionic liquids (ILs) provide a promising solution in many industrial applications, such as
solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to …
solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to …
3D-QSAR, molecular docking, molecular dynamic simulation, and ADMET study of bioactive compounds against candida albicans
Candida albicans has developed significant levels of resistance to traditional antifungals,
posing a danger to world health. In this research, the potential inhibitory of a class of twenty …
posing a danger to world health. In this research, the potential inhibitory of a class of twenty …
Convolutional neural network model based on 2D fingerprint for bioactivity prediction
Determining and modeling the possible behaviour and actions of molecules requires
investigating the basic structural features and physicochemical properties that determine …
investigating the basic structural features and physicochemical properties that determine …
A review of quantitative structure-activity relationship: the development and current status of data sets, molecular descriptors and mathematical models
J Li, T Zhao, Q Yang, S Du, L Xu - Chemometrics and Intelligent Laboratory …, 2024 - Elsevier
Abstract Developing Quantitative Structure-Activity Relationship (QSAR) models applicable
to general molecules is of great significance for molecular design in many disciplines. This …
to general molecules is of great significance for molecular design in many disciplines. This …
Binary quantitative activity-activity relationship (QAAR) studies to explore selective HDAC8 inhibitors: In light of mathematical models, DFT-based calculation and …
Abstract Histone deacetylase 8 (HDAC8) selectivity over other HDACs is a major concern of
interest, since HDAC8 has been implicated as a potential drug target of many diseases …
interest, since HDAC8 has been implicated as a potential drug target of many diseases …
MetaCGRP is a high-precision meta-model for large-scale identification of CGRP inhibitors using multi-view information
N Schaduangrat, P Khemawoot, A Jiso… - Scientific Reports, 2024 - nature.com
Migraine is considered one of the debilitating primary headache conditions with an
estimated worldwide occurrence of approximately 14–15%, contributing highly to factors …
estimated worldwide occurrence of approximately 14–15%, contributing highly to factors …
Application of Machine Learning Methods to Predict the Air Half-Lives of Persistent Organic Pollutants
Y Zhang, L Xie, D Zhang, X Xu, L Xu - Molecules, 2023 - mdpi.com
Persistent organic pollutants (POPs) are ubiquitous and bioaccumulative, posing potential
and long-term threats to human health and the ecological environment. Quantitative …
and long-term threats to human health and the ecological environment. Quantitative …
Risk substance identification of asphalt VOCs integrating machine learning and network pharmacology
L Ge, J Li, Z Lin, X Zhang, Y Yao, G Cheng… - … Research Part D …, 2024 - Elsevier
Asphalt releases volatile organic compounds (VOCs) during paving processes, posing risks
to workers and the environment. The complex composition of asphalt and the evolving of …
to workers and the environment. The complex composition of asphalt and the evolving of …