Petri Nets in Systems Biology presents a rigorous and coherent framework for modeling and analyzing complex biological systems. Positioned at the intersection of computer science, biomedicine, bioinformatics, and target-based drug discovery, the book demonstrates how Petri nets naturally capture key characteristics of biological processes, including concurrency, synchronization, causality, stochastic, and fuzzy behavior.

The book introduces fundamental Petri net concepts and progressively extends them to address core problems in systems biology, such as the modeling of metabolic networks, gene regulatory systems, signal transduction pathways, and cellular control mechanisms. Both qualitative and quantitative analysis techniques are covered, including invariant analysis, reachability, structural properties, stochastic modeling, and hybrid extensions.

A strong emphasis is placed on modularity, compositional modeling, and biological interpretability, enabling readers to construct scalable and reusable models that remain closely aligned with underlying biological knowledge. Through carefully selected running examples and case studies, the book illustrates how Petri net technologies can be used to simulate system dynamics, analyze regulatory structure, and gain insight into emergent behaviors of complex biological networks.

Intended for researchers, graduate students, and advanced practitioners, Petri Nets in Systems Biology serves as both an accessible introduction and a comprehensive reference. It provides the theoretical foundations and practical tools necessary for applying Petri nets to contemporary challenges in computational and systems biology.