Deep Learning in Bioinformatics

Deep Learning in Bioinformatics: Techniques and Applications in Practice, Second Edition

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 in systems biology.

The book also presents theoretical and practical successes of deep learning in bioinformatics, pointing out problems and suggesting future research directions. This updated edition includes several new chapters, applications, and examples for new Deep Learning advances and techniques.

Dr. Izadkhah provides valuable insights and will help researchers use deep learning techniques in their biological and bioinformatics studies.

Highlights

Introduces deep learning in an easy-to-understand way

Presents how deep learning can be utilized for addressing many important problems in bioinformatics

Provides state-of-the-art algorithms in deep learning and bioinformatics

Introduces deep learning libraries in bioinformatics