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
Protein Structure Prediction by Artificial Intelligence
Methods and Tools for Predicting Protein Folding from Free Energy Change upon Mutation
Deep Neural Network-assisted Full-System Quantum Mechanical (FQM) Calculations of Proteins
Transfer Learning-assisted Full-System Quantum Mechanical (FQM) Calculations of Proteins
Protein Interaction Prediction with Artificial Intelligence
Protein Function Annotation with Machine Learning
Machine Learning-driven ab initio Protein Design
Large Language Models of Protein Systems
Outlook
| ISBN | 9783527352159 |
|---|---|
| Article number | 9783527352159 |
| Media type | Book |
| Edition number | 1. Auflage |
| Copyright year | 2025 |
| Publisher | Wiley-VCH |
| Length | 256 pages |
| Illustrations | 30 SW-Abb., 50 Farbabb. |
| Language | English |
