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Deep Learning for Genomics Data-Driven Approaches for Genomics Applications in Life Sciences and Biotechnology.
Learn concepts, methodologies, and applications of deep learning for building predictive models from complex genomics data sets to overcome challenges in the life sciences and biotechnology industries Key Features Apply deep learning algorithms to solve real-world problems in the field of genomics E...
| Call Number: | Libro Electrónico |
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| Main Author: | |
| Format: | Electronic eBook |
| Language: | Inglés |
| Published: |
[S.l.] :
PACKT PUBLISHING LIMITED,
2022.
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| Subjects: | |
| Online Access: | Texto completo (Requiere registro previo con correo institucional) |
Table of Contents:
- Table of Contents Introducing Machine Learning for Genomics Genomics Data Analysis Machine Learning Methods for Genomic Applications Deep Learning for Genomics Introducing Convolutional Neural Networks for Genomics Recurrent Neural Networks in Genomics Unsupervised Deep Learning with Autoencoders GANs for Improving Models in Genomics Building and Tuning Deep Learning Models Model Interpretability in Genomics Model Deployment and Monitoring Challenges, Pitfalls, and Best Practices for Deep Learning in Genomics.