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
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science & Techn.
Dateigröße
ISBN-13
978-0-443-22298-6 (9780443222986)
Schweitzer Klassifikation
1. Deep Learning Ensembles in Translational Bioinformatics2. Recursive Feature Elimination and Multi Support Vector Machine in Healthcare Analytics3. Sensors-enabled Biomedical Decision Support System using Deep Learning and Fuzzy Logic4. Prediction of Alzheimer's Disease Using Densely Convolutional Neural Network5. Brain Tumor Detection from MRI Images using Shallow CNN6. Pandemic Disease Detection Using Diffusional Convolutional Neural Network7. Multiview Technique and Shallow CNN with Dropouts to Predict Antiviral Peptides8. Deep Learning Methods for Protein Classification9. Biosensors-based Identification of Antibiotic Resistance in Bacteria10. Deep Learning for Fervent Gene Expression Analysis11. Machine Learning-enforced Bioinformatics Approaches for Drug Discovery and Development12. Role of Deep Learning in Predicting Drug Formulations and Delivery Systems13. Deep Learning in Computer-aided Drug Design: A Case Study14. Protein Structure Prediction with RNN and CNN: A Case Study15. Generative Adversarial Networks in Protein and Ligand Structure Generation: A Case Study16. Artificial Neural Networks for Prediction of Psychological Threats: A Case Study
