Satoh H. Drug Development Supported by Informatics 2024 torrent

Textbook in PDF format

This book describes several informatics methods for regression, classification, clustering, prediction and generation. It treats several types of neural networks, e.g., convolutional neural network (CNN), recurrent neural network (RNN), graph neural network (GNN) and generative adversarial network (GAN) with different types of learning methods, including self-supervised learning, unsupervised learning, transfer learning and reinforcement learning. It discusses also advanced language models, data assimilation and image processing, which are extensively used in current molecular and material science.
Regarding application targets, this book covers all steps in the basic research phase, i.e., prediction of property and activity, molecular design, in silico evalua-tion of designed molecules, reaction and synthetic design, and analysis and eval-uation of synthesized molecules. The topics extend to biomaterials design, phar-maceutical formulation and drug delivery. Interdisciplinary collaborations between advanced microscopies and informatics to “see” a better view of biomolecules or living cells are also presented. From the view of applied informatics, the content of this book is related to chemoinformatics, bioinformatics, materials informatics and measurement/metrology informatics