Predictive modeling of asthma drug properties using machine learning and topological indices in a MATLAB based QSPR study

Machine learning is a vital tool in advancing drug development by accurately predicting the physical, chemical, and biological properties of various compounds. This study utilizes MATLAB program-based algorithms to calculate topological indices and machine learning algorithms to explore their abilit...

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Veröffentlicht in:	Scientific reports Jg. 15; H. 1; S. 30373 - 25
Hauptverfasser:	Bayati, Jalal Hatem Hussein, Mahboob, Abid, Amin, Laiba, Rasheed, Muhammad Waheed, Alameri, Abdu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 19.08.2025 Nature Publishing Group Nature Portfolio
Schlagworte:	639/166/898 639/166/985 639/638 639/705 Algorithms Anti-Asthmatic Agents - chemistry Anti-Asthmatic Agents - pharmacology Anti-Asthmatic Agents - therapeutic use Asthma Asthma - drug therapy Asthma drugs Biological properties Chemical properties Drug development Drug Discovery - methods Extreme gradient boosting Graphs Humanities and Social Sciences Humans Inflammation Learning algorithms Machine Learning MATLAB and Python algorithm Molecular structure multidisciplinary Physical properties Quantitative Structure-Activity Relationship Random forest Reducible topological descriptors Science Science (multidisciplinary) Trends MATLAB and Python algorithm Reducible topological descriptors Random forest Extreme gradient boosting Asthma drugs Machine learning
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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