Well stablished methods for determining metabolic fluxes such as Flux Balance Analysis (FBA) work under the hypothesis that biological systems maximize growth rate.
FBA hypothesis has been questioned as it is not always able to represent the correct flux allocation or to predict product outcome. This is the case of systems where a regulatory phenomenon such as the glucose overflow observed in yeast determines cellular metabolism.
Other methods have been proposed, such as parsimonious FBA or geometric centered solution, however all these proposals are biased, either by the method itself or by the choice of the method used.
The use of the principle or maximum entropy allows for the least biased choice of flux allocation and still allowing for compliance with mass balances and thermodynamic consistency of the flux allocation in the metabolic network.
This workshop gathers international experts in the topic, each one from a different point of view, from classical thermodynamics to information entropy to address a biological problem.
The workshop is possible thanks to project FOVI230173 funded by ANID Chile.
How genomics illuminates estimations of cellular metabolism?
How the principle of maximun entropy produces the least biased and most likely prediction?
Professor
Politecnico di Torino
Research Associate Professor Biofisika Institute
Professor & Entrepreneur
University of California, San Diego
Associate Professor
Universidad de los Andes
Professor
Pontificia Universidad Católica de Valparaíso
Assistant Professor
Universidad Tecnológica Metropolitana
Assistant Professor
Universidad Adolfo Ibáñez
Professor
Politecnico di Torino
Research Associate Professor Biofisika Institute
Associate Professor
Universidad de los Andes
Assistant Professor
Universidad Tecnológica Metropolitana