BackgroundOver 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 expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications.ResultsOptFlux is an open-source and modular software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed OptKnock algorithm. It also allows the use of stoichiometric metabolic models for (i) phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis, Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes, (ii) Metabolic Flux Analysis, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes.OptFlux also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization algorithms.The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. OptFlux has a visualization module that allows the analysis of the model structure that is compatible with the layout information of Cell Designer, allowing the superimposition of simulation results with the model graph.ConclusionsThe OptFlux software is freely available, together with documentation and other resources, thus bridging the gap from research in strain optimization algorithms and the final users. It is a valuable platform for researchers in the field that have available a number of useful tools. Its open-source nature invites contributions by all those interested in making their methods available for the community.Given its plug-in based architecture it can be extended with new functionalities. Currently, several plug-ins are being developed, including network topology analysis tools and the integration with Boolean network based regulatory models.
Benign hereditary chorea (BHC) is an autosomaldominant disorder of early onset characterized by a slowly progressing or nonprogressing chorea, without cognitive decline or other progressive neurologic dysfunction, but also by the existence of heterogeneity of the clinical presentation within and among families. The genetic cause of BHC is the presence of either point mutations or deletions in the thyroid transcription factor 1 gene (TITF1). We studied a Portuguese BHC family composed of two probands: a mother and her only son. The patients were identified in a neurology out-patient clinic showing mainly involuntary choreiform movements since childhood, myoclonic jerks, falls, and dysarthria. We performed magnetic resonance imaging (MRI), electroencephalogram (EEG), nerve conduction studies, thyroid ultrasound scan, biochemical thyroid tests, and electrocardiogram (ECG). We excluded Huntington disease by appropriate genetic testing and sequenced the entire TITF1 gene for both patients. The patients showed MRI alterations: (1) in the mother, abnormal hyperintense pallida and cortical cerebral/cerebellar atrophy; and (2) in the son, small hyperintense foci in the cerebellum and subtle enlargement of the fourth ventricle. Sequence analysis of the TITF1 gene in these patients revealed the presence of a heterozygous C > T substitution at nucleotide 745, leading to the replacement of a glutamine at position 249 for a premature stop codon. A previously undescribed nonsense mutation in the TITF1 gene was identified as being the genetic cause of BHC in this family.
This work proposes JECoLi -a novel Java-based library for the implementation of metaheuristic optimization algorithms with a focus on Genetic and Evolutionary Computation based methods. The library was developed based on the principles of flexibility, usability, adaptability, modularity, extensibility, transparency, scalability, robustness and computational efficiency. The project is opensource, so JECoLi is made available under the GPL license, together with extensive documentation and examples, all included in a community Wiki-based web site (http://darwin.di.uminho.pt/jecoli). JECoLi has been/is being used in several research projects that helped to shape its evolution, ranging application fields from Bioinformatics, to Data Mining and Computer Network optimization.
BackgroundFlux analysis methods lie at the core of Metabolic Engineering (ME), providing methods for phenotype simulation that allow the determination of flux distributions under different conditions. Although many constraint-based modeling software tools have been developed and published, none provides a free user-friendly application that makes available the full portfolio of flux analysis methods.ResultsThis work presents Constraint-based Flux Analysis (CBFA), an open-source software application for flux analysis in metabolic models that implements several methods for phenotype prediction, allowing users to define constraints associated with measured fluxes and/or flux ratios, together with environmental conditions (e.g. media) and reaction/gene knockouts. CBFA identifies the set of applicable methods based on the constraints defined from user inputs, encompassing algebraic and constraint-based simulation methods. The integration of CBFA within the OptFlux framework for ME enables the utilization of different model formats and standards and the integration with complementary methods for phenotype simulation and visualization of results.ConclusionsA general-purpose and flexible application is proposed that is independent of the origin of the constraints defined for a given simulation. The aim is to provide a simple to use software tool focused on the application of several flux prediction methods.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-014-0123-1) contains supplementary material, which is available to authorized users.
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