Artificial intelligence in drug discovery. (2020)

• Record Type: Book
• Further Information: Note: Edited by Nathan Brown.
• Editors: Brown, Nathan
• Contents: 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
• Edition: 1st
• Publisher Details: Cambridge : Royal Society of Chemistry
• Publication Date: 2020
• Extent: 1 online resource
• Subjects: 615.190028563; Drugs -- Design -- Computer simulation; Artificial intelligence -- Medical applications
• Languages: English
• ISBNs: 9781788016841; 9781839160547
• Related ISBNs: 9781788015479
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.