English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

OLIVEIRA, Rafael David. Development of a computational tool for metabolic flux analysis with labeled carbon. 2017. 87 p. Dissertation (Master of Science) – Polytechnic School, University of São Paulo, São Paulo, 2017. 13C-Metabolic Flux Analysis (13C-MFA) has become a high-precision technique to estimate metabolic fluxes and get insights into metabolism. This method consists of experimental procedures, measurement techniques and data analysis calculations. In this context, metabolic engineering research groups demand accurate and suitable computational tools to perform the calculations. A computational tool was implemented in MATLAB platform that performs 13C-MFA calculation, using metabolite and cumomer balances, as well as a module to estimate the fluxes and a module to quantify their uncertainty. The program was validated with some classical cases from literature. From the flux estimates of Pseudomonas sp. LFM046, it was identified that the microorganism possibly uses the Pentose Phosphate Pathway along with the Entner-Doudoroff Pathway for Polyhydroxyalkanoate (PHA) biosynthesis. From the optimal experimental design for a generic Pseudomonas network, it was possible to conclude that glucose labeled at atom five is the best option to determine the flux in the Pentose Phosphate Pathway with smaller uncertainty. Key-words: 13C-metabolic flux analysis, metabolic engineering, modeling, parameter estimation, Pseudomonas, PHA

Desenvolvimento de uma ferramenta computacional para a análise de fluxos metabólicos empregando carbono marcado.