Wang / Chen / Zhang Computational Intelligence in Protein-Ligand Interaction Analysis

1. Auflage 2024
ISBN: 978-0-12-824435-7
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 310 Seiten

Computational Intelligence in Protein-Ligand Interaction Analysis presents computational techniques for predicting protein-ligand interactions, recognizing protein interaction sites, and identifying protein drug targets. The book emphasizes novel approaches to protein-ligand interactions, including machine learning and deep learning, presenting a state-of-the-art suite of skills for researchers. The volume represents a resource for scientists, detailing the fundamentals of computational methods, showing how to use computational algorithms to study protein interaction data, and giving scientific explanations for biological data through computational intelligence. Fourteen chapters offer a comprehensive guide to protein interaction data and computational intelligence methods for protein-ligand interactions. - Presents a guide to computational techniques for protein-ligand interaction analysis - Guides researchers in developing advanced computational intelligence methods for the protein-ligand problem - Identifies appropriate computational tools for various problems - Demonstrates the use of advanced techniques such as vector machine, neural networks, and machine learning - Offers the computational, mathematical and statistical skills researchers need

Bing Wang is Dean in the School of Electrical & Electronics Information at Anhui University of Technology, in China. He received his PhD in bioinformatics from the University of Technology, China, on protein-protein interaction site prediction. He has held postdoctoral positions in machine learning, chemoinformatics, and biomedical information engineering at the Universities of Louisville and Vanderbilt, in the USA. He has published over 120 papers, is a senior member of IEEE, and serves on the editorial board of several journals.

Autoren/Hrsg.

Wang, Bing

Chen, Peng

Zhang, Jun