Python for Systems Pharmacology and Network Medicine: Building Predictive Models of Drug Action, Disease Networks, Polypharmacology

Reactive PublishingPython for Systems Pharmacology and Network Medicine offers a practical, code-first introduction to applying Python in one of the most dynamic areas of modern drug discovery and biomedical research.Systems pharmacology and network medicine are transforming how we understand drug action, disease mechanisms, and therapeutic opportunities. This book bridges the gap between computational methods and biological complexity by teaching you how to build predictive models that integrate drug-target interactions, disease networks, and polypharmacology using Python.What You'll Learn: - Core concepts in network medicine and systems pharmacology- How to construct and analyze biological networks (protein-protein, drug-target, disease networks)- Building predictive models of drug action and side effects- Techniques for studying polypharmacology and drug repurposing- Data integration from major pharmacological and biomedical databases- Practical implementation using key Python libraries (NetworkX, Pandas, NumPy, SciPy, scikit-learn, and more)- Visualization of complex biological networks and model interpretabilityWritten for researchers, pharmacologists, bioinformaticians, and data scientists working at the intersection of medicine and computation, this book emphasizes clear explanations, reproducible code examples, and real-world applications.Whether you are exploring drug mechanisms, mapping disease networks, or developing next-generation predictive models, Python for Systems Pharmacology and Network Medicine provides the computational foundation you need to advance your work in this rapidly evolving field.Perfect for: - Graduate students and researchers in pharmacology, systems biology, and bioinformatics- Computational biologists transitioning into drug discovery- Data scientists interested in biomedical applications

Pages: 464, Paperback, Independently published