Qspr Qsar Analysis Using Smiles And Quasi Smiles
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QSPR/QSAR Analysis Using SMILES and Quasi-SMILES
This contributed volume overviews recently presented approaches for carrying out QSPR/QSAR analysis by using a simplifying molecular input-line entry system (SMILES) to represent the molecular structure. In contrast to traditional SMILES, quasi-SMILES is a sequence of special symbols-codes that reflect molecular features and codes of experimental conditions. SMILES and quasi-SMILES serve as a basis to develop QSPR/QSAR as well Nano-QSPR/QSAR via the Monte Carlo calculation that provides the so-called optimal descriptors for QSPR/QSAR models. The book presents a reliable technology for developing Nano-QSPR/QSAR while it also includes the description of the algorithms of the Monte Carlo optimization. It discusses the theory and practice of the technique of variational authodecoders (VAEs) based on SMILES and analyses in detail the index of ideality of correlation (IIC) and the correlation intensity index (CII) which are new criteria for the predictive potential of the model. The mathematical apparatus used is simple so that students of relevant specializations can easily follow. This volume is a valuable contribution to the field and will be of great interest to developers of models of physicochemical properties and biological activity, chemical technologists, and toxicologists involved in the area of drug design.
Materials Informatics I
This contributed volume explores the integration of machine learning and cheminformatics within materials science, focusing on predictive modeling techniques. It begins with foundational concepts in materials informatics and cheminformatics, emphasizing quantitative structure-property relationships (QSPR). The volume then presents various methods and tools, including advanced QSPR models, quantitative read-across structure-property relationship (q-RASPR) models, optimization strategies with minimal data, and in silico studies using different descriptors. Additionally, it explores machine learning algorithms and their applications in materials science, alongside innovative modeling approaches for quantum-theoretic properties. Overall, the book serves as a comprehensive resource for understanding and applying machine learning in the study and development of advanced materials and is a useful tool for students, researchers and professionals working in these areas.
New Frontiers in Nanochemistry: Concepts, Theories, and Trends
The final volume of this new innovative and informative three-volume set explains and explores the essential basic and advanced concepts from various areas within the nanosciences. This volume primarily focuses on increasing awareness of sustainable nanochemistry, meaning the social and economic impact of nanochemistry, in order to mitigate ecological resource depletion and to promote the exploration of nature as a resource for future benefits. This volume adopts a pharmacological lens, examining the multitude of ways in which nano-research can contribute to the development of pharmaceutical drugs and paying particular attention to toxicology and renewable energy within nanochemistry. Under the vast expertise of the editor, the volume contains 34 entries contributed by renowned international scientists and scholars. The content in this volume covers topics such as anti-HIV agents, ecotoxicology, solar cells and photovoltaic phenomena, spectral-SAR, and more—alphabetically organized and accompanied by equations, figures, and brief letters in order to emphasize the potential applications of the concepts discussed.