Description

Deep Learning for Biology: Harness AI to Solve Real-World Biology Problems.

Deep Learning for Biology: A Practical Guide to Applying AI in Life Sciences

Connect the worlds of modern machine learning and biological research with this hands-on, project-focused guide. Whether you come from a background in biology, software development, or data science, Deep Learning for Biology provides the knowledge and practical skills needed to create deep learning models for solving complex biological challenges.

Authors Charles Ravarani and Natasha Latysheva take you through practical projects that apply deep learning techniques to areas such as DNA analysis, protein modeling, biological networks, medical imaging, and microscopy. Each chapter presents a complete mini-project, offering step-by-step guidance on building, training, evaluating, and interpreting deep learning models using real biological datasets.

Through practical examples, you’ll learn how to:

• Develop models for biological challenges such as gene regulation, protein function prediction, drug interaction analysis, and cancer detection.
• Apply powerful architectures including convolutional neural networks, transformers, graph neural networks, and autoencoders.
• Work with Python and interactive notebooks to gain hands-on experience.
• Build transferable problem-solving skills that apply beyond computational biology.

Whether you are entering the field of computational biology, expanding your machine learning expertise, or seeking to apply AI methods to biological research, this book offers a practical and accessible pathway to understanding and using deep learning in the life sciences.