Approaches genome-scale coverage. The k-ecoli457 is a genome-scale kinetic model of Escherichia coli metabolism. It was parameterized by combining a machine-learning algorithm and the Ensemble Modelling (EM) formalism. This model contains more of 450 reactions and 330 metabolites.
Provides a flexible and adaptable approach to infer gene activity. This algorithm is an improved version of MultiMM, an application that assists users in simulated and real gene expression data, confirming well-known biological results and yielding better agreement with fluxomics data. This Bayesian modeling framework improves outlier handling by explicitly modeling network and other uncertainty yielding improved gene activity state estimates.
Assists in the annotation of metabolic models using both manual and automated techniques. Metingear tries to facilitate the integration of chemical structure into genome-scale models. This tool provides a dynamic annotation system allowing each entity to hold multiple annotations of the same type. It works in two steps: (1) the candidate matches are searched; (2) when the candidates have been found the direct match is attempted between names.
Allows analysis of metabolic networks. PMFA enables users to find metabolic flux modes that explains the variance in gene expression or fluxomic data collected from heterogeneous environmental conditions, without requiring a fixed set of predefined pathways to be given. The method combines stoichiometric flux analysis and principal component analysis. It can be applied to genome-scale metabolic network. The software includes a sparse variant of PMFA that favors flux modes containing a small number of reactions.
Provides functions for continuous glucose monitoring (CGM) studies. CGManalyzer is an analytic tool that can be used to analyze a CGM study from the very beginning to the end, including reading and displaying data, calculating regular statistics (e.g., mean, median, standard deviation, confidence interval) and nonlinear statistics, conducting group comparison and displaying results. The software can be applied to data measured by various existing CGM devices such as FreeStyle Libre, Glutalor, Dexcom, Medtronic CGM.
Estimates the dynamic promoter activity for promoters that change their activity in response to the environment. PromAct permits to infer known promoter activity profiles with accuracy and is able to estimate the correct scale of promoter activity. For that, this tool uses only protein expression and biomass data as inputs without use of underlying assumptions about the organism, experiment, time resolution or mode of regulation of the promoter of interest.
Calculates the similarity between lipidomes. LUX Score is a single metric based solely upon an identity matrix for exchange values, which does not account for quantitative changes. It facilitates inter-species functional association that are applied in comparative genomics. This workflow is customizable in regard to the complexity of the lipidome study. This approach is also compatible with high-throughput lipidomics.
Provides a metabolic modeling framework. DRUM serves to model dynamically intracellular processes where accumulation of intracellular metabolites is important by using metabolic knowledge. One of the originality of this tool lies in the coupling of macroscopic and intracellular modeling approaches. It aims to better apprehend intracellular mechanisms at the metabolic level when the biological system undergoes environmental perturbations and can be used to optimize bioprocess.
A tool that computes how each possible flux measurement outcome affects the range of other reactions. MMF can be used to make distributions of fluxes and their predicted impact, select key reactions in the network and prioritize measurements.
Obtains optimal designs of metabolic networks satisfying multiple objectives. PSOMCS uses particle swarm optimization along with the direct calculation of concept of constrained minimal cut sets from the stoichiometric matrix. It finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. The tool can be used to identify knockouts which will force optimal desired behaviors in large and genome scale metabolic networks.
Provides a pipeline for optimizing metabolic engineering targets. OptPipe is based on combining several optimization solutions obtained from distinct algorithms and ranking them according to several objectives, such as biomass and target production. This general framework can be applied to any organism and target product. It also significantly supports metabolic engineering tasks.
Performs model and constraint consistency checking. MC3 is useful for two operations: (1) identification of potential connectivity and topological issues for a given stoichiometric matrix and (2) description of issues that arise during constraint-based optimization. This tool is able to identify the conditions for dead-end metabolites. It can be useful for the scientist community for documenting and reporting issues with each published model.
Assists users with the extraction of features on multi-omics data. DSFPSO is a particle swarm optimization (PSO) with dynamic scale-free network. Four types of velocity updating strategies are used in this algorithm for fully considering the heterogeneity of particles and the connecting between neighbors. This method can be used to extract genes associated with cancers.
Returns the estimated biomass composition in amino acids, nucleotides (NTPs) and deoxynucleotides (dNTPs) for an organism, from files with selected sequences and transcriptomic data. Biomass is a java application that allows users to obtain results rapidly. The obtained data can be directly included in the biomass equation of a genome-scale metabolic model. The results obtained using this method and the described procedure are fairly close to experimental data, showing that the estimation of amino acid and nucleotide compositions from genome information and transcriptomic data are a good alternative when no experimental data is available.
Allows for the creation of networks composed of metabolic relationships, protein and protein-DNA interactions. BioNetBuilder is a plugin for Cytoscape that permits associations from comparative genomics regardless of what database the gene product originally came from or what data format the integration databases support. It does not require a rigid database schema, file-format or data-model that new data sources must conform to.
Assists researchers in obtaining comprehensive biosynthesis target molecules based on the BKM-React reactions. Biosynther is a web-based tool that implements user-customized pathway search engines by removing some nodes and/or edges to find the biosynthesis pathways. It allows researchers to interactively explore, step by step, the biosynthetic potentials of precursor chemicals. The software can be useful in metabolic engineering.
Provides a metabolic model from data extracted from a rapid sampled pulse experiment. MMT sets up a metabolic network to re-engineer a chosen cell's metabolism. It applies a circular process of modeling, simulation and validation including splines. Moreover, the software uses a program generation to supplies a specialized simulator to speed up parameter fitting and other computations.