Thermodynamics in Metabolic Pathways

This lecture explores the application of thermodynamics in metabolic pathways, focusing on the use of Flux Balance Analysis and the formulation of the problem as a Mixed Integer Linear Programming. It discusses the constraints imposed by thermodynamics, the role of bi-directional reactions, and the group contribution method for estimating Gibbs free energy. The uncertainty in linear regression models and the impact of experimental errors are also covered. Additionally, it delves into the influence of factors like pH and ionic strength on free energy calculations, as well as the effect of crowding conditions on metabolic pathway feasibility.

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related lectures (99)

Related concepts (97)

ChE-411: Principles and applications of systems biology

The course introduces and develops the key concepts from systems biology and systems engineering in the context of complex biological networks. The lectures elaborate on techniques and methods to mode

Measurement uncertainty

In metrology, measurement uncertainty is the expression of the statistical dispersion of the values attributed to a measured quantity. All measurements are subject to uncertainty and a measurement result is complete only when it is accompanied by a statement of the associated uncertainty, such as the standard deviation. By international agreement, this uncertainty has a probabilistic basis and reflects incomplete knowledge of the quantity value. It is a non-negative parameter.

Experimental uncertainty analysis

Experimental uncertainty analysis is a technique that analyses a derived quantity, based on the uncertainties in the experimentally measured quantities that are used in some form of mathematical relationship ("model") to calculate that derived quantity. The model used to convert the measurements into the derived quantity is usually based on fundamental principles of a science or engineering discipline. The uncertainty has two components, namely, bias (related to accuracy) and the unavoidable random variation that occurs when making repeated measurements (related to precision).

Uncertainty quantification

Uncertainty quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known. An example would be to predict the acceleration of a human body in a head-on crash with another car: even if the speed was exactly known, small differences in the manufacturing of individual cars, how tightly every bolt has been tightened, etc.

Metabolic pathway

In biochemistry, a metabolic pathway is a linked series of chemical reactions occurring within a cell. The reactants, products, and intermediates of an enzymatic reaction are known as metabolites, which are modified by a sequence of chemical reactions catalyzed by enzymes. In most cases of a metabolic pathway, the product of one enzyme acts as the substrate for the next. However, side products are considered waste and removed from the cell. These enzymes often require dietary minerals, vitamins, and other cofactors to function.

Sensitivity analysis

Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be divided and allocated to different sources of uncertainty in its inputs. A related practice is uncertainty analysis, which has a greater focus on uncertainty quantification and propagation of uncertainty; ideally, uncertainty and sensitivity analysis should be run in tandem.

Bioenergetics: Cellular Energy Generation ChE-411: Principles and applications of systems biology

Explores cellular energy generation through bioenergetics and metabolic pathways.

Flux Balance Analysis: Optimization and Phenotypic Phase Planes ChE-411: Principles and applications of systems biology

Explores Flux Balance Analysis principles, optimization, Phenotypic Phase Planes, and bioenergetics in metabolic networks.

Metabolic Flux Balance Analysis ChE-411: Principles and applications of systems biology

Covers modeling and analyzing complex biological networks, focusing on metabolism and signaling, using techniques like flux balance analysis and kinetic modeling.

Thermodynamics and Energetics I ME-251: Thermodynamics and energetics I

Delves into thermodynamics basics, calculating energy changes, constructing tables, and using Maxwell relations for thermodynamic relations.

Polymer Collapse: Covolume and Free Energy PHYS-441: Statistical physics of biomacromolecules

Explores polymer collapse, emphasizing covolume and free energy in the process.