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Prediction of Protein Secondary Structure
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This second edition volume expands on the previous edition with updates on the latest methods, resources, and studies concerning analysis and prediction of various structural and functional aspects of proteins and ncRNAs. The chapters in this book cover topics such as secondary structure characterization and prediction; the use and impact of AI (including AlphaFold, large language models, and deep neural networks) in the protein structure prediction field; methods and resources for the prediction of posttranslational modifications, residue-residue contacts, subcellular localization, intrinsic disorder, protein-ligand interactions, and protein aggregation; analysis of cryo-EM data; and analysis of noncoding RNAs in the context of human diseases. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions and surveys of the respective topics, list the necessary materials and methods, cover step-by-step instructions on how to use predictive tools and interpret their results, and provide tips on troubleshooting and avoiding known pitfalls.
Cutting-edge and thorough, Prediction of Protein Secondary Structure, Second Edition is a valuable resource for anyone interested in understanding the dynamic and growing field of the protein structure prediction.
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