Introduction to Systems Biology Workbook for Flipped-classroom Teaching

• Main Author: Sauter, Thomas (auth)
• Other Authors: Albrecht, Marco (auth)
• Format: Electronic Book Chapter
• Language: English
• Published: Cambridge Open Book Publishers 2023
• Subjects: Research methods: general; Research & information: general; Research & development management; Data capture & analysis; Data mining; Biology, life sciences; Medical bioinformatics; systems biology;introduction;interdisciplinary framework;mathematical concepts;biological entities;physics concepts
• Online Access: OAPEN Library: download the publication; OAPEN Library: description of the publication

This book is an introduction to the language of systems biology, which is spoken among many disciplines, from biology to engineering. Authors Thomas Sauter and Marco Albrecht draw on a multidisciplinary background and evidence-based learning to facilitate the understanding of biochemical networks, metabolic modeling and system dynamics. Their pedagogic approach briefly highlights core ideas of concepts in a broader interdisciplinary framework to guide a more effective deep dive thereafter. The learning journey starts with the purity of mathematical concepts, reveals its power to connect biological entities in structure and time, and finally introduces physics concepts to tightly align abstraction with reality. This workbook is all about self-paced learning, supports the flipped-classroom concept, and kick-starts with scientific evidence on studying. Each chapter comes with links to external YouTube videos, learning checklists, and Integrated real-world examples to gain confidence in thinking across scientific perspectives. The result is an integrated approach that opens a line of communication between theory and application, enabling readers to actively learn as they read. This overview of capturing and analyzing the behavior of biological systems will interest adherers of systems biology and network analysis, as well as related fields such as bioinformatics, biology, cybernetics, and data science.