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Springer Bayesian Networks in R: Systems Biology Guide

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Description

Master Bayesian network modeling and inference with this specialized guide from Springer. This book introduces essential concepts through practical examples using the open-source statistical environment R. Designed for hands-on learning, the text gradually increases in sophistication across chapters, providing exercises and solutions to help you experiment with theory and concepts effectively. The content focuses on applications within systems biology, with a specific emphasis on modeling signaling mechanisms and pathways from high-throughput molecular data. Whether you are studying statistical modeling or biological systems, this resource provides a structured approach to working with complex data in R.

Key Features

Learn Bayesian network modeling and inference using the open-source R statistical environment.

Explore specialized applications in systems biology, specifically for modeling pathways and signaling mechanisms.

Develop practical skills through a gradual increase in chapter sophistication and complexity.

Gain hands-on experience with included exercises and solutions for testing theoretical concepts.

Analyze high-throughput molecular data through the lens of Bayesian network theory.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
27 April 2013
Listed Since
06 December 2012

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