Deep Learning in Bioinformatics: Techniques and Applications in Practice

Deep Learning in Bioinformatics: Techniques and Applications in Practice book cover

Deep Learning in Bioinformatics: Techniques and Applications in Practice

Author(s): Izadkhah (Author)

  • Publisher: Academic Press
  • Publication Date: 8 Jan. 2022
  • Edition: 1st
  • Language: English
  • Print length: 380 pages
  • ISBN-10: 0128238224
  • ISBN-13: 9780128238226

Book Description

Deep Learning in Bioinformatics: Techniques and Applications in Practice introduces the topic in an easy-to-understand way, exploring how it can be utilized for addressing important problems in bioinformatics, including drug discovery, de novo molecular design, sequence analysis, protein structure prediction, gene expression regulation, protein classification, biomedical image processing and diagnosis, biomolecule interaction prediction, and in systems biology. The book also presents theoretical and practical successes of deep learning in bioinformatics, pointing out problems and suggesting future research directions. Dr. Izadkhah provides valuable insights and will help researchers use deep learning techniques in their biological and bioinformatics studies.

  • Introduces deep learning in an easy-to-understand way
  • Presents how deep learning can be utilized for addressing some important problems in bioinformatics
  • Presents the state-of-the-art algorithms in deep learning and bioinformatics
  • Introduces deep learning libraries in bioinformatics

Editorial Reviews

Review

Provides the most current research advances in the field of computational modeling and its applications in science and engineering

From the Back Cover

Deep Learning in Bioinformatics: Techniques and Applications in Practice introduces Deep Learning in an easy-to-understand way, and then explores how Deep Learning can be utilized for addressing important problems in bioinformatics, including drug discovery, de novo molecular design, sequence analysis, protein structure prediction, gene expression regulation, protein classification, biomedical image processing and diagnosis, biomolecule interaction prediction and systems biology. The book also presents the recent theoretical and practical successes of Deep Learning in the bioinformatics domain, pointing out the problems which are suitable to utilize Deep Learning and suggest future research directions. Dr. Izadkhah provides valuable insights and will help researchers to use Deep Learning techniques in their biological and bioinformatics studies as a starting point.

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