Artificial Intelligence in Drug Discovery
Royal Society of Chemistry (Verlag)
978-1-78801-547-9 (ISBN)
Introduction;
The History of Artificial Intelligence and Chemistry;
Chemical Topic Modelling – An Unsupervised Approach Originating from Text-mining to Organize Chemical Data;
Deep Learning and Chemical Data;
Concepts and Applications of Conformal Prediction in Computational Drug Discovery;
Non-applicability Domain. The Benefits of Defining “I don’t know” in Artificial Intelligence;
Predicting Protein-Ligand Binding-Affinities;
Virtual Screening with Convolutional Neural Networks;
Machine Learning in the Area of Molecular Dynamics Simulations;
Compound Design Using Generative Neural Networks;
Junction Tree Variational Autoencoder for Molecular Graph Generation;
AI via Matched Molecular Pair Analysis;
Molecular de novo Design Through Deep Generative Models;
Active Learning for Drug Discovery and Automated Data Curation;
Data-driven Prediction of Organic Reaction Outcomes;
ChemOS: an Orchestration Software to Democratize Autonomous Discovery;
Summary and Outlook
Erscheinungsdatum | 12.11.2020 |
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Reihe/Serie | Drug Discovery ; Volume 75 |
Verlagsort | Cambridge |
Sprache | englisch |
Maße | 156 x 234 mm |
Gewicht | 803 g |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Naturwissenschaften ► Biologie ► Biochemie | |
Naturwissenschaften ► Biologie ► Genetik / Molekularbiologie | |
ISBN-10 | 1-78801-547-9 / 1788015479 |
ISBN-13 | 978-1-78801-547-9 / 9781788015479 |
Zustand | Neuware |
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