Machine Learning in Protein Science
Efficient Prediction of Protein Structures and Properties
Machine Learning in Protein Science
Efficient Prediction of Protein Structures and Properties
This unique practical reference for protein scientist shows how to harness the power of machine learning for quick and efficient full quantum mechanical calculations of protein structures and properties.
Introduction
Introduction
Fundamentals of Theoretical Calculations on Protein Systems
Machine Learning-driven Ab Initio Protein Design
Prediction of Protein Mutation Effects
Structure Prediction with AlphaFold
Deep Neural Network-assisted Full-System Quantum Mechanical (FQM) Calculations of Proteins
Transfer Learning-assisted Full-System Quantum Mechanical (FQM) Calculations of Proteins
Universal Protein Feature Dictionary and Framework for Protein Property Predictions
Recurrent Neural Network-assisted Thermostability Predictions of Protein Systems
Machine Learning-assisted Full-System Quantum Mechanical (FQM) Calculations of Enzymes in Industrial Environmnts
Outlook
| ISBN | 9783527352159 |
|---|---|
| Artikelnummer | 9783527352159 |
| Medientyp | Buch |
| Auflage | 1. Auflage |
| Copyrightjahr | 2025 |
| Verlag | Wiley-VCH |
| Umfang | 320 Seiten |
| Abbildungen | 30 SW-Abb., 50 Farbabb. |
| Sprache | Englisch |
