Genome-scale metabolic reconstruction software tools | Metabolic engineering data analysis
Reconstructing a metabolic network consists in drafting the list of the biochemical reactions that an organism can carry out together with information on cellular boundaries, a biomass assembly reaction, and exchange fluxes with the external environment. Building up models able to represent the different functional cellular states is universally recognized as a tricky task that requires intensive manual effort and much additional information besides genome sequence.
Allows management, analysis, simulation and visualization of integrated collections of genome, pathway and regulatory data. Pathway Tools is a bioinformatics software environment around a type of model-organism database called Pathway/Genome Database (PGDB). The software can manipulate genome data, metabolic networks and regulatory networks. For each datatype, it provides query, visualization, editing and analysis functions. It also provides visual tools for analysis of omics data sets, and tools for the analysis of biological networks.
Enables users to reconstruct genome-scale metabolic models for any organism that has its genome sequenced. merlin is composed of two main modules, (1) one developed specifically to help on the genome annotation stage with dedicated tools and graphical user interfaces (GUIs), and (2) the other oriented to the remaining stages. The software also provides tools for curating the model. Triage, a tool for identifying the metabolites transported by each transmembrane protein and its transporter family is included in merlin.
Constructs a universal draft model of metabolism by downloading all reactions and metabolites in the BiGG database into a single SBML file. CarveMe can automates curation tasks to build a final universal model. It is based on a universal biomass equation and offers no blocked or unbalanced reactions. This tool can be used to create microbial community models by merging selected sets of single-species models into community-scale networks.
A user-friendly web application designed to compare, integrate and visualize meta-omics data from gut microbial communities (metagenomics, metatranscriptomics, metametabolomics, and metaproteomics) within a standard web browser with minimal effort and input.
Allows users to reconstruct, analyze, simulate and visualize genome-scale metabolic models (GEMs). RAVEN Toolbox permits users to input GEM(s) for one or more template organisms, their corresponding protein sequences, and protein sequences of the target organism. A GEM for target organism is then constructed based on orthology between the protein sequences of target organism and the organisms of template models. Some of its functionalities are also available through the browser-based GUI BioMet Toolbox.
An easy-to-use stand-alone application that can visualize and convert KGML formatted XML-files into multiple output formats. KEGGtranslator, unlike other translators, supports a plethora of output formats, is able to augment the information in translated documents (e.g. MIRIAM annotations) beyond the scope of the KGML document, and amends missing components to fragmentary reactions within the pathway to allow simulations on those.
Implements important quality control and assurance measures (QC/QA), which are crucial for the construction of high-quality genome-scale biochemical networks. rBioNet consists of three parts: (i) a metabolite creator with associated metabolite database (MetDB); (ii) a reaction creator with reaction database (RxnDB); and (iii) a reconstruction creator. rBioNet is embedded within the COBRA toolbox enabling iterative approach of reconstruction, validation and debugging.
A comprehensive curated map of human metabolism presented utilizing the Google Maps application program interface (API) for highly responsive interactive navigation within a platform that facilitates queries and custom data visualization. Omics data and flux distributions resulting from simulations can be visualized in in a network context via an extension to the COBRA Toolbox. All users may post suggestions for refinement. Each suggestion is forwarded to virtual metabolic human (VMH) curators for consideration when planning further curation effort.
Facilitates exploration of highly-connected and comprehensive human metabolic data and identification of metabolic subnetworks of interest. Recon2Neo4j provides two major components: i) a graph database for the human metabolism data and ii) a parser for translating the JSON representation into the SBML and SIF formats. Recon2Neo4j has been designed to offer a computational framework for exploring data from the Recon2 human metabolic reconstruction model. A powerful feature of the Recon2Neo4j is facilitating querying and exploration of integrated metabolic data, which adds to the functionality provided by other systems biology software, such as e.g. cySBML.
Allows users to estimate the structural robustness even in genome-scale metabolic models (GSMMs). networkRobustnessToolbox is a rigorous and quantitative approach for the structural robustness of metabolic networks. It can measure its ability to tolerate random reactions knockouts and quantify the structural fragility of metabolic networks based on the probability of failure (PoF).
Creates strain design strategies using metabolite analogues (Mas). MARSI is composed of three parts: (i) marsi db, for constructing chemical analogues databases; (ii) marsi optimize, for computing knockout-based designs, knockout based and over- as well as down-regulated designs and; (iii) marsi chem for browsing into chemical analogues repositories. The application can also serve for designs implementation by allowing users to detect candidate Mas.
Provides a multi implementation platform dedicated to probabilistic annotation. ProbAnno is a software available through a web application, a standalone python package as well as an API. The software permits to annotate protein sequences in a proteome by detecting similarities with known functions of other proteins. Then, the software attributes a probability to each annotation. The tool is compatible with various software such as openCOBRA, Mackinac and ModelSEED.
Handles structural information. ssbio is built around four mains functions: (i) sequenced-based tools; (ii) structure-based tools; (iii) a pipeline that permits users to building genome scale models and (iv) a function for importing and convert data from on line databases. In addition, users can add supplementary packages for specific required tasks such as predict kinetic folding rate. The application can also be executed through Jupyter notebooks.
Allows users to link gene expression and splice isoform data to genome-scale metabolic models. GEMsplice is a method for incorporating RNA-Seq data at the splice-isoform level into a metabolic model. The software performs accurate predictions of human metabolic behavior and cancer metabolism. It was tested by building breast cancer-versus-normal genome-scale models and by comparing predictions with available results on metabolic pathways affected by breast cancer.
Combines ModelSEED’s ability to automatically reconstruct metabolic models with COBRApy’s advanced analysis capabilities to bridge the differences between the two frameworks and to facilitate the study of the metabolic potential of microorganisms. Mackinac allows the comprehensive storage of all the information associated with the models in the COBRA model object, and provides direct access to many of the functions available from this web service, such as functions to reconstruct, gap fill, and optimize genome-scale metabolic models (GEMs).
Detects incomplete parts of network reconstructions based on the following approach: identifying elements (compounds) of catalytic cycles. ASBIG recognizes inconsistencies in existing genome-scale metabolic network reconstructions. This method facilitates network validation and automated gap detection in primary metabolism contributing considerably to the quality improvement of metabolic models. This tool combines conceptual approaches of autocatalytic metabolites and scope analysis.
Represents a genome-scale metabolic network model. AraGEM covers primary metabolism for a compartmentalized plant cell that rests on the Arabidopsis genome. This tool is able to predict classical photorespiratory cycle. It is useful for in silico functional analysis and to obtain hypotheses for working about plant metabolism.
Serves for simultaneous genome-scale metabolic reconstruction of multiple related species that leverages on the growing availability of sequenced genomes. CoReCo is a comparative metabolic reconstruction framework that reconstructs gapless metabolic models for a large number of fungal species. It allows users to annotate complete genomes to reconstruct genome-scale metabolic networks.
Detects potential gap reactions. CanOe computes metabolons in a global metabolic network populated by reactions known to be catalyzed in the target organism. It offers a list of candidate genes for each gap reactions. It can aid bioanalysts to confirm putative annotations for local orphan reactions by automatically mining the wealth of a metabolic context.