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TNA4OptFlux : a software tool for the analysis of strain optimization strategies

BACKGROUND:Rational approaches for Metabolic Engineering (ME) deal with the identification of modifications that improve the microbes' production capabilities of target compounds. One of the major challenges created by strain optimization algorithms used in these ME problems is the interpretation of the changes that lead to a given overproduction. Often, a single gene knockout induces changes in the fluxes of s...

Computational tools for large-scale biological network analysis

Tese de doutoramento em Informática ; The surge of the field of Bioinformatics, among other contributions, provided biological researchers with powerful computational methods for processing and analysing the large amount of data coming from recent biological experimental techniques such as genome sequencing and other omics. Naturally, this led to the opening of new avenues of biological research among which is...

A study of the short and long-term regulation of E. coli metabolic pathways

The present study addresses the regulatory network of Escherichia coli and offers a global view of the short- and long-term regulation of its metabolic pathways. The regulatory mechanisms responsible for key metabolic activities and the structure behind such mechanisms are detailed. Most metabolic functions are dependent on the activity of transcriptional regulators over gene expression - the so-called long-ter...

Interpreting the regulatory interplay in E. coli metabolic pathways

Many regulatory processes in the cell are based on the control of gene expression through the interaction of transcription factors. However, enzymatic regulation often overlays transcriptional regulation and even, in some metabolic pathways, enzymatic regulation prevails. The present study addresses the regulatory network of Escherichia coli and offers a global view of the regulation of its metabolic pathways. ...

Highlighting metabolic strategies using network analysis over strain optimizati...

The field of Metabolic Engineering has been growing, sup- ported by the increase in the number of annotated genomes and genome- scale metabolic models. In silico strain optimization methods allow to create mutant strains able to overproduce certain metabolites of interest in Biotechnology. Thus, it is possible to reach (near-) optimal solutions, i.e. strains that provide the desired phenotype in computational p...

Caracterização de sorotipos em linhagens do gênero Salmonella isoladas de difer...

Foram caracterizados os sorotipos, o perfil de sensibilidade microbiana e os achados clínico-epidemiológicos em 53 linhagens do gênero Salmonella isoladas de 41 cães, nove equinos e três bovinos, acometidos por diferentes manifestações clínicas entre 1997 e 2007. Salmonella Typhimurium (45,3%), Salmonella enterica (22,6%), Salmonella Enteritidis (7,5%), Salmonella enterica subsp enterica 4,5,12i (5,7%), Salmone...

OptFlux : an open-source software platform for in silico metabolic engineering

Background: Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other ex...

Data integration issues in the reconstruction of the genome-scale metabolic mod...

Genome-scale model reconstruction represents a major tool in the field of Metabolic Engineering .This paper reports on a study about data integration issues in the process of genome- scale reconstruction of the metabolic model of the bacterium Zymomonas mobilis, a promising organism for bioethanol production. Data is retrieved from the Entrez Gene, KEGG, BioCyc and Brenda databases, and the several processes in...

OptFlux : a software for metabolic engineering

Natural computation meta-heuristics for the in silico optimization of microbial...

Background: One of the greatest challenges in Metabolic Engineering is to develop quantitative models and algorithms to identify a set of genetic manipulations that will result in a microbial strain with a desirable metabolic phenotype which typically means having a high yield/productivity. This challenge is not only due to the inherent complexity of the metabolic and regulatory networks, but also to the lack o...