Genome-scale metabolic models (GEMs) are computational models that represent the entire set of metabolic reactions in an organism, allowing researchers to simulate and analyze metabolic networks at a systems level. These models are integral for understanding cellular metabolism, guiding metabolic engineering, and optimizing biotechnological applications.

Genome-scale Metabolic Models

Genome-scale metabolic models

Computational models are abstract representations that use algorithms and mathematical formulations to simulate complex systems and predict their behavior under various conditions. They are essential tools in fields like physics, biology, and economics, providing insights that are often unattainable through traditional experimental methods alone.

computational models

metabolic reactions

Metabolic networks are complex systems of interconnected biochemical reactions that sustain life by converting substrates into energy and essential biomolecules. They are crucial for understanding cellular physiology, disease mechanisms, and biotechnological applications such as metabolic engineering and synthetic biology.

metabolic networks

systems level

Cellular metabolism comprises all chemical reactions within cells that enable them to maintain life, grow, reproduce, and respond to their environments. It is divided into catabolic pathways that break down molecules to release energy and anabolic pathways that build complex molecules from simpler ones.

cellular metabolism

Metabolic engineering involves the optimization of cellular processes to increase the production of specific substances, often using recombinant DNA technology. This field is pivotal in biotechnology for improving yields in pharmaceuticals, biofuels, and other valuable chemicals by altering metabolic pathways in microorganisms and plants.

metabolic engineering

Biotechnological applications leverage biological systems and organisms to develop products and technologies that enhance human health, agriculture, and environmental sustainability. These applications span across diverse fields such as genetic engineering, pharmaceuticals, and biofuels, driving innovation and addressing global challenges.

Your Courses

Relevant Degrees

Your Lessons