Sinopsis
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.
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Acerca de los autores
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.
Peng Chen is a Professor in the Institute of Physical Science and Information Technology, and the School of the Internet, at Anhui University, China. He received his PhD from the University of Science and Technology of China (USTC). He has held international roles in Hong Kong, the USA, and Saudi Arabia. He was previously Associate Professor at the Hefei Institute of Intelligent Machines, with the Chinese Academy of Sciences. His research interests include machine learning, and data mining, and he has published over 100 papers.
Jun Zhang is a Professor at Anhui University, China, and is an expert in the field of computational intelligence.
De la contraportada
The volume and speed of scientific data has transformed the life sciences, leading to an acceleration in bioinformatics, computational biology, and quantitative biology. In turn, researchers in bioinformatics and computational biology now require a suite of computational, mathematical, and statistical skills in order to handle large amounts of data. Computational Intelligence in Protein-Ligand Interaction Analysis presents computational techniques for predicting protein-ligand interactions, recognising 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, demonstrating ways computational tools and techniques can be applied for effective research on protein-ligand interaction.
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COMPU INT IN PROTEIN-LIGAND INTE AN
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