Metabolic Network Analysis: Modeling Cellular Metabolism

Modern biology generates massive amounts of genomic data, but understanding how these components work together to sustain life requires a systems-level approach. Metabolic network analysis allows you to model the biochemical reactions inside a cell to predict its behavior, growth, and evolutionary constraints. This text-only course guides you from the fundamental principles of cellular metabolism to the computational modeling of complex biological networks. You will gain a clear understanding of how to analyze metabolic pathways, simulate cellular growth under different conditions, and interpret simulation results using modern constraint-based modeling approaches. What you'll learn: Understand the core biological and mathematical principles behind metabolic networks; Reconstruct metabolic pathways from genomic and biochemical data; Apply Flux Balance Analysis to predict cellular phenotypes and growth rates; Configure constraints and objective functions to simulate genetic and environmental changes; Explore modern computational modeling concepts and python-based COBRA frameworks; Analyze network behavior to identify key drug targets or metabolic engineering strategies. The course begins with foundational definitions of metabolism and network biology before moving into the mathematics of stoichiometric matrices. You will then progress to practical simulation techniques and modern computational workflows used in systems biology research today. This course is designed for beginners in bioinformatics, biotechnology, or systems biology, requiring no advanced programming or mathematical background to start. Start reading today to unlock the power of computational metabolic modeling.