| Description |
1 online resource (xv, 363 pages) |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
| Contents |
Why Life Science? -- A Review of Machine Learning -- An Introduction of Python Ecosystem for Deep Learning -- Basic Structure of Neural Networks -- Training Multilayer Neural Networks -- Classification in Bioinformation -- Introduction to Deep Learning -- Medical Image Processing: an Insight to Convolutional Neural Networks -- Popular Deep Learning Image Classifiers -- Electrocardiogram (ECG) Arrhythmia Classification -- Autoencoders and Deep Generative Models in Bioinformatics -- Recurrent Neural Networks: Generating New Molecules and Proteins Sequence Classification -- Application, Challenge, and Suggestion. |
| Summary |
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. |
| Subject |
Bioinformatics.
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Machine learning.
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Computational Biology |
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Machine Learning |
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Bio-informatique.
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Apprentissage automatique.
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Bioinformatics
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Machine learning
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| Other Form: |
Print version: 9780128238363 |
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Print version: 0128238224 9780128238226 (OCoLC)1268111169 |
| ISBN |
9780128238363 (electronic bk.) |
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0128238364 (electronic bk.) |
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9780128238226 |
| Standard No. |
AU@ 000070477205 |
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