Deep Learning in Bioinformatics

Techniques and Applications in Practice

Habib Izadkhah (Autor)

Buch | Softcover

380 Seiten

2022
Academic Press Inc (Verlag)
978-0-12-823822-6 (ISBN)

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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.

Dr. Habib Izadkhah is an Associate Professor at the Department of Computer Science, University of Tabriz, Iran. He worked in the industry for a decade as a software engineer before becoming an academic. His research interests include algorithms and graphs, software engineering, and bioinformatics. More recently he has been working on the developing and applying Deep Learning to a variety of problems, dealing with biomedical images, speech recognition, text understanding, and generative models. He has contributed to various research projects, authored a number of research papers in international conferences, workshops, and journals, and also has written five books, including Source Code Modularization: Theory and Techniques from Springer.

1. Why Life Science?
2. A Review of Machine Learning
3. An Introduction of Python Ecosystem for Deep Learning
4. Basic Structure of Neural Networks
5. Training Multi-Layer Neural Networks
6. Classification in Bioinformatics
7. Introduction to Deep learning
8. Medical Image Processing: An Insight to Convolutional Neural Networks
9. Popular Deep Learning Image Classifiers
10. Electrocardiogram (ECG) Arrhythmia Classification
11. Autoencoders and Deep Generative Models in Bioinformatics
12. Recurrent Neural Networks: Generating New Molecules and Proteins Sequence Classification
13. Application, Challenge, and Suggestion

Erscheinungsdatum	18.01.2022
Verlagsort	San Diego
Sprache	englisch
Maße	191 x 235 mm
Gewicht	790 g
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie
	Naturwissenschaften ► Biologie
	Technik ► Medizintechnik
ISBN-10	0-12-823822-4 / 0128238224
ISBN-13	978-0-12-823822-6 / 9780128238226
Zustand	Neuware