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Can I read Machine Learning in Bioinformatics of Protein Sequences: Algorithms, Databases and Resources for Modern Protein Bioinformatics (377 Pages) on EtoBox?

Machine Learning in Bioinformatics of Protein Sequences: Algorithms, Databases and Resources for Modern Protein Bioinformatics (377 Pages) by Łukasz Kurgan is a nonfiction available to read on EtoBox.

What is Machine Learning in Bioinformatics of Protein Sequences: Algorithms, Databases and Resources for Modern Protein Bioinformatics (377 Pages) about?

"Machine Learning in Bioinformatics of Protein Sequences guides readers around the rapidly advancing world of cutting-edge machine learning applications in the protein bioinformatics field. Edited by bioinformatics expert, Dr Lukasz Kurgan, and with contributions by a dozen of accomplished researchers, this book provides a holistic view of the structural bioinformatics by covering a broad spectrum of algorithms, databases and software resources for the efficient and accurate prediction and characterization of functional and structural aspects of proteins. It spotlights key advances which include deep neural networks, natural language processing-based sequence embedding and covers a wide range of predictions which comprise of tertiary structure, secondary structure, residue contacts, intrinsic disorder, protein, peptide and nucleic acids-binding sites, hotspots, post-translational modification sites, and protein function. This volume is loaded with practical information that identifies and describes leading predictive tools, useful databases, web servers, and modern software platforms for the development of novel predictive tools"-- Provided by publisher

Who reads Machine Learning in Bioinformatics of Protein Sequences: Algorithms, Databases and Resources for Modern Protein Bioinformatics (377 Pages)?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Łukasz Kurgan
Publisher
World Scientific Publishing Co Pte Ltd
Published
2022
Language
EN
ISBN
9789811258572
Category
nonfiction
Subjects
Science, Biology, Stem

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