A First Course in Systems Biology, 2nd Edition

A First Course in Systems Biology, 2nd Edition by Eberhard Voit provides an introduction to the growing field of systems biology, with particular emphasis on computational modeling and its application to biological systems. Designed for advanced undergraduate and graduate students, the book combines biological concepts with mathematical and computational approaches for studying complex biological processes.

About the Book

The book begins with the fundamentals of systems biology modeling and gradually develops the concepts and methods needed to construct and analyze computational models. It also introduces the molecular components that form biological systems before examining case studies from systems biology and synthetic biology.

The approach is designed to give students both a conceptual foundation and practical methods for approaching biological questions through theoretical and computational techniques.

Key Topics and Concepts

The second edition covers a wide range of systems biology concepts, including:

• Fundamentals of biological modeling
• Computational models of biological systems
• Model design and default modules
• Molecular inventories and biological networks
• Gene regulation and transcription factors
• Michaelis-Menten kinetics and enzyme inhibition
• Parameter estimation
• Limit cycles and chaos
• Hysteresis and system adaptation
• Nonlinear nullclines
• Models of cellular differentiation
• PBPK (physiologically based pharmacokinetic) models
• Elementary modes
• Systems biology and synthetic biology

Computational Modeling in Biology

A central theme of the book is the use of mathematical and computational models to understand biological systems. Rather than treating modeling as an isolated mathematical exercise, the text connects model construction and analysis to biological questions.

New material in this edition expands the treatment of model representations, parameter estimation, nonlinear behavior, adaptation to persistent signals, and other concepts important for analyzing dynamic biological systems.

From Fundamentals to Current Research

The book also introduces case studies that represent areas at the forefront of systems biology and synthetic biology. References to primary research literature help students connect the concepts introduced in the text with the scientific literature and current research practices.

This combination makes the book useful not only for learning the fundamentals of systems biology but also for preparing students to read research papers and undertake specialized projects.

Learning Through Exercises

The text combines instructional material with practical exercises. Small-scale problems provide hands-on experience with modeling concepts, while larger and often open-ended questions encourage students to explore biological systems more deeply and develop their own analytical approaches.

This format supports both classroom teaching and independent study.

Who Should Read This Book?

This textbook is particularly suitable for:

• Advanced undergraduate students
• Graduate students
• Students of systems biology
• Computational biology and bioinformatics students
• Students of molecular and quantitative biology
• Researchers beginning computational systems biology projects
• Students preparing for specialized courses in biological modeling

Final Thoughts

A First Course in Systems Biology, 2nd Edition provides a practical introduction to using mathematical and computational models to investigate biological systems. Its combination of modeling fundamentals, biological case studies, primary literature, and hands-on exercises makes it a useful foundation for students entering systems biology, synthetic biology, computational biology, and related quantitative fields.

Book Information

Title: A First Course in Systems Biology, 2nd Edition
Author: Eberhard Voit
Publisher: Garland Science
Publication Date: 5 September 2017
Edition: 2nd
Language: English
Print Length: 468 pages
ISBN-10: 0815345682
ISBN-13: 978-0815345688
Subjects: Systems Biology, Computational Biology, Mathematical Biology, Biological Modeling, Synthetic Biology, Bioinformatics, Quantitative Biology, Systems Biology Modeling