Deep Learning Applications in Translational Bioinformatics

Khalid Raza,Debmalya Barh,Deepak Singh,Naeem Ahmad

• Verlag: Academic Press
• Jahr: 2024
• ISBN:
  9780443222986
• Thema: Tecnología e ingeniería
• Thema: Ingeniería general

Deep Learning Applications in Translational Bioinformatics, a new volume in the Advances in Ubiquitous Sensing Application for Healthcare series, offers a detailed overview of basic bioinformatics, deep learning, various applications of deep learning in translational bioinformatics including deep learning ensembles, deep learning in protein classification, detection of various diseases, prediction of antiviral peptides, identification of antibiotic resistance, computer aided drug design and drug formulation.

This new volume helps researchers working in the field of machine learning and bioinformatics to foster future research and development in ensemble deep learning and inspire new bioinformatics applications that cannot be attained by using traditional machine learning models.

• Addresses the practical application of deep learning algorithms to a wide range of bioinformatics challenges
• Presents integrative and multidisciplinary approaches to ubiquitous healthcare
• Includes case studies to illustrate the concepts discussed

Inhaltsverzeichnis

• Cover image
• Title page
• Table of Contents
• Copyright
• List of contributors
• About the editors
• Chapter 1. Deep learning ensembles in translational bioinformatics
• Chapter 2. Recursive feature elimination and multisupport vector machine in healthcare analytics
• Chapter 3. Sensor-enabled biomedical decision support system using deep learning and fuzzy logic
• Chapter 4. Prediction of Alzheimer’s disease using densely convolutional neural network
• Chapter 5. Brain tumor detection from magnetic resonance imaging images using shallow convolutional neural network
• Chapter 6. Multiview learning with shallow 1D-CNN for anticancer activity classification of therapeutic peptides
• Chapter 7. Deep learning methods for protein classification
• Chapter 8. Biosensors-based identification of antibiotic resistance in bacteria
• Chapter 9. Deep learning for vehement gene expression exploration
• Chapter 10. Machine learning-enforced bioinformatics approaches for drug discovery and development
• Chapter 11. Role of deep learning in predicting drug formulations and delivery systems
• Chapter 12. Deep learning in computer-aided drug design: a case study
• Chapter 13. Protein structure prediction with recurrent neural network and convolutional neural network: a case study
• Chapter 14. Generative adversarial networks in protein and ligand structure generation: a case study
• Chapter 15. Artificial neural networks for prediction of psychological threats: a case study
• Index