Devisetty Deep Learning for Genomics

Data-driven approaches for genomics applications in life sciences and biotechnology
1. Auflage 2022
ISBN: 978-1-80461-301-6
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 270 Seiten

No detailed description available for "Deep Learning for Genomics".

Autoren/Hrsg.

Devisetty, Upendra Kumar

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision

Inhaltsverzeichnis

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

Über Autor(innen)

Devisetty Upendra Kumar:
Dr. Upendra Kumar Devisetty is a Senior Data Science Manager at Greenlight Biosciences where he leads a team of Bioinformatics Scientists, Data Scientists, Business Intelligence Analysts, and Project managers to support the various Bioinformatics and Data Science projects at GreenLight Biosciences and contribute to a cleaner environment, healthier people, and a stronger food supply chain.