Searches protein database using a translated nucleotide query. BLASTX is a BLAST search application that compares the six-frame conceptual translation products of a nucleotide query sequence (both strands) against a protein sequence database. This application can also work in Blast2Sequences mode and can send BLAST searches over the network to public NCBI server if desired.
Provides a web-based analytical pipeline for high-throughput metabolomics studies. MetaboAnalyst aims to offer a variety of commonly used procedures for metabolomic data processing, normalization, multivariate statistical analysis, as well as data annotation. The current implementation focuses on exploratory statistical analysis, functional interpretation, and advanced statistics for translational metabolomics studies. This tool is also available as desktop version.
Allows users to analyze and visualize liquid chromatography – mass spectrometry (LC-MS) data. PiMP is a comprehensive and integrated web enabled pipeline that consists of five tasks: (1) project administration, (2) data upload, (3) quality control, (4) analysis parameters and (5) data interpretation. Users can define the experimental design, specify metadata and share the project with collaborators with a chosen level of permission. It aims at automatization and standardization of metabolomics analysis.
Allows users to simulate chemical reaction-diffusion networks. pSSAlib is an open source application offering a library of multiple known partial-propensity stochastic simulation algorithms (SSAs) with the aim to assist users in choosing a specific formulation. The application permits to import specifications of biochemical models as well as features for statistical analysis and visualization of simulation results.
A web-based tool for the visualization and analysis of cellular pathways. Its primary map summarizes the metabolism in biological systems as annotated to date. Nodes in the map correspond to various chemical compounds and edges represent series of enzymatic reactions.
A web server that offers the possibility to link metabolites identified in untargeted metabolomics experiments within the context of genome-scale reconstructed metabolic networks. The analysis pipeline comprises mapping metabolomics data onto the specific metabolic network of an organism, then applying graph-based methods and advanced visualization tools to enhance data analysis.
Simulates microbial degradation based on a hierarchically ordered set of principal metabolic transformations. CATABOL is a probabilistic scheme that was able to reproduce experimentally documented transformations of perfluorinated chemicals (PFCs). It can also be used for simulating catabolism and predicting biodegradation products in ready biodegradability tests. The set of transformations includes 141 abiotic and biologically mediated reactions.
Manages multi-omics datasets visualization within KEGG pathway diagrams. PaintOmics is dedicated to pathway analysis and proposes functionalities for converting names and/or identifiers, performing pathway enrichment and network analysis. This program is able to handle data from multiple type of omics measurement. Results can be displayed by pathways summary, classification, networks, enrichment or by detailed pathway view.
Aims users to detect metabolites by annotation of pathways from cross-omics data. MarVis-Suite serves especially for the extraction, clustering, and visualization of metabolic markers from data originating of non-targeted experiments. It provides interactive desktop user interfaces for interactive inspection of data clusters, and supplies specialized functions for the analysis of data from non-targeted mass spectrometry (MS) experiments.
Develops many interactive web-based databases and software to help the life-scientists understand the complexity of systems biology. Systems biology efforts focus on understanding cellular networks, protein interactions involved in cell signaling, mechanisms of cell survival and apoptosis leading to development or identification of drug candidates against a variety of diseases.
Provides a bioinformatics framework for the visualization and interpretation of metabolomic and expression profiling data in the context of human metabolism. MetScape allows users to build and analyze networks of genes and compounds, identify enriched pathways from expression profiling data, and visualize changes in metabolite data. MetScape uses an internal relational database that integrates data from KEGG and EHMN.
An open standard based on the XML markup language. The purpose of CellML is to store and exchange computer-based mathematical models. CellML allows scientists to share models even if they are using different model-building software. It also enables them to reuse components from one model in another, thus accelerating model building.
Aims to integrate and analyze metabolomics experiment data. MeltDB is a program that can be applied for the description and analysis of metabolomic experiments. This program hosts over 30 experiments predominantly from gas chromatography-mass spectrometry (GC/MS) measurements. Moreover, this tool includes an API allowing users to evaluate novel methods and algorithms for the preprocessing of metabolomic datasets.
Elucidates the topological and flux connectivity features of genome-scale metabolic networks and enables the global identification of blocked reactions, equivalent knockouts, and sets of affected reactions. The FCF computational procedure allows one to determine whether any two metabolic fluxes, v1 and v2, are (i) fully coupled, if a non-zero flux for v1 implies a non-zero, but also a fixed flux for v2 and vice versa; (ii) partially coupled, if a non-zero flux for v1 implies a non-zero, though variable, flux for v2 and vice versa; or (iii) directionally coupled, if a non-zero flux for v1 implies a non-zero flux for v2 but not necessarily the reverse. Due to its wide range of features and applicability to genome-scale networks, the FCF procedure provides a useful framework for both modelers and experimentalists seeking to extract biologically meaningful information from metabolic reconstructions.
Provides current experimental knowledge of the proximal hepatic insulin signaling network. This model provides a sequential method of postprandial hepatic control of glucose and lipid by insulin, according to which delayed aPKC switch-off contributes to selective hepatic insulin resistance. This model is quantitatively informed by two in vivo data sets from rodent studies, where hepatic insulin signaling was measured after refeeding or after various patterns (pulsatile/constant/T2D) of pre-hepatic insulin infusion.
Annotates metabolites in high precision mass spectrometry data. MassTRIX marks the identified chemical compounds on KEGG pathway maps using the KEGG/API. Selected genes or enzymes can be highlighted, e.g. to represent information on gene transcription or differences in the gene complement of different bacterial strains.
A curated database that contains information about biochemical reactions, their kinetic rate equations with parameters and experimental conditions. All the data are manually curated and annotated by biological experts, supported by automated consistency checks. SABIO-RK can be accessed via web-based user interfaces or automatically via web services that allow direct data access by other tools. Both interfaces support the export of the data together with its annotations in SBML (Systems Biology Markup Language), e.g. for import in modelling tools.
Provides a comprehensive flux balance analysis framework for microbial communities. OptCom relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. This modeling framework is general enough to capture any type of interactions (positive, negative or combination of both) for any number of species (or guilds) involved. In addition, OptCom is able to explain in vivo observations in terms of the levels of optimality of growth for each participant of the community.
A powerful analytical method for the identification of biologically meaningful metabolic subpathways. Subpathway-GM integrates ‘interesting genes’ and ‘interesting metabolites’ related to the study condition (e.g. disease) into the corresponding enzyme and metabolite nodes (referred to as signature nodes) within the metabolic pathway. We then analyzed lenient distance similarities of signature nodes within the pathway structure to locate key metabolic cascade subpathway regions. Finally, a hypergeometric test was used to evaluate the enrichment significance of these subpathway regions.
An integrated biological pathway database designed to support pathway discovery in the fields of proteomics, transcriptomics, metabolomics and systems biology. The key goal of IPAVS is to provide biologists access to expert-curated pathways from experimental data belonging to specific biological contexts related to cell types, tissues, organs and diseases. IPAVS currently integrates over 500 human pathways (consisting of 24, 574 interactions) that include metabolic-, signaling- and disease-related pathways, drug-action pathways and several large process maps collated from other pathway resources. IPAVS web interface allows biologists to browse and search pathway resources and provides tools for data import, management, visualization and analysis to support the interpretation of biological data in light of cellular processes.
Facilitates an analysis of the metabolomic and transcriptional profiling data in the context of cellular reaction network. GAM service provides a way for a quick interactive analysis of the data to identify the most regulated metabolic subnetworks. The service supports multiple input formats, including results from widely-used DESeq2 and limma pipelines, provides automatic selection of recommended parameter values and uses a range of maximum-weight connected subgraph (MWCS) solvers yielding good suboptimal solutions in a time frame of 30 s.
A unified web interface for visualizing metabolic networks, reconstructing metabolic networks from annotated genome data, visualizing experimental data in the context of metabolic networks and investigating the construction of novel, transgenic pathways. This simple, user-friendly interface is tightly integrated with the comparative genomics tools of MicrobesOnline.
Predicts pathways and constructs mathematical models to systematically analyse metabolic systems. PASMet provides four main functionalities: (i) prediction, (ii) construction, (iii) simulation and (iv) analysis. It includes an interface to access various algorithms for predicting probable regulatory mechanisms along with generating mathematical models from time-series data, simulating metabolic behaviors and determining metabolic bottlenecks in the model.
A modular software pipeline for integrated analysis of environmental sequence information. MetaPathways performs a series of popular analyses for taxonomic profiling and functional potential with limited data handling, allowing researchers to spend their time analyzing their data instead of performing complicated data transformations. MetaPathways v2.0 incorporating a graphical user interface (GUI) and refined task management methods.
Generates associations between Kyoto Encyclopedia of Genes and Genomes (KEGG) and LIPID MAPS structure Database (LMSD) databases. NICELips consists of several components integrated into a workflow and it is the first tool to provide an efficient and consistent procedure for linking lipid compound databases. It provides a full overview of all lipid species in the cell, and particularly in the context of metabolic pathways that comprise all the chemical interactions and transformations between lipid compounds and enzymes.
Uses the statistical significance of changes in gene or protein expression to create a functional metabolic model that most accurately recapitulates the expression dynamics. MADE is a method for mapping expression data from a set of environmental, genetic or temporal conditions onto a metabolic network model without the need for arbitrary expression thresholds. It integrates gene or protein expression data and a metabolic model without a priori determination of activity thresholds.
Integrates enzymatic transformations with metabolite structural similarity, mass spectral similarity and empirical associations to generate richly connected metabolic networks. This open source, web-based or desktop software, written in the R programming language, leverages KEGG and PubChem databases to derive associations between metabolites even in cases where biochemical domain or molecular annotations are unknown.
Compares metabolic pathway activities from metabolite profiles. The PAPi package allows to quickly compare metabolic pathways activities between different experimental conditions. Using the identified metabolites and their respective abundances as input, it calculates pathways' Activity Scores, which represents the potential metabolic pathways activities and allows their comparison between conditions. It also performs principal components analysis and analysis of variance or t-test to investigate differences in activity level between experimental conditions. In addition, PAPi generates comparative graphs highlighting up- and down-regulated pathway activity.
A toolbox that facilitates importing and exporting models represented in the Systems Biology Markup Language (SBML) in and out of the MATLAB environment and provides functionality that enables an experienced user of either SBML or MATLAB to combine the computing power of MATLAB with the portability and exchangeability of an SBML model. SBMLToolbox supports all levels and versions of SBML.
An open source flexible and customizable tool enabling users to predict biochemical reactions and pathways. ReactPRED allows to create customizable reaction rule set automatically from an input reaction set. Moreover, the tool is able to simulate pathways or reactions in a synthetic or retrosynthetic mode allowing a larger scope of applications for drug metabolism and biochemical engineering.
Supports modelers of biochemical reaction pathways. JigCell provides a model builder, run manager, comparator, and automatic parameter estimator. It permits users to understand and explain the underlying mechanisms driving the physiology of the organisms under study. This toolbox can be used to define a system to be modelled using Systems Biology Markup Language (SBML), display data in an organized manner, specify a set of specifications for simulation runs and define models in terms of components for the purpose of being combined in a larger model.
Provides the user with the flexibility to model a variety of biochemical pathways from signal transduction to metabolism. Cell++ is a stochastic simulation environment with the capacity to study a wide variety of biochemical processes within a spatial context. Combining a cellular automata engine with Brownian dynamics, this software is able to simulate the bulk properties of large quantities of small molecules while simultaneously allowing more accurate representations of large molecules that can display more complex behavior.
A Cytoscape plugin dedicated to the inference and visualization of high-resolution mass spectrometry data sets. The inference is achieved using a defined list of putative biochemical transformations. The flexibility provided by this tool allows for isolation of transformation types in order to facilitate a focused analysis. A wide range of correlation analysis tools allows an even stronger inference of network connections than possible with mass difference analysis alone. In addition to the rich interactions provided by Cytoscape, the plugin offers a convenient way to visualize some topological properties of the networks.
Provides functional analysis without prior knowledge of detailed kinetic data. MonaLisa is based on the Petri net (PN) formalism and focuses on decomposition methods to identify functional modules at steady state. Besides, the software can also be applied to elementary mode analysis and enables a visual inspection of the analysis results. Furthermore, MonaLisa implements interfaces to many tools in systems biology, PN world and graph-theory.
Division for Bioinformatics, Innsbruck Medical University, Innsbruck, Austria; Health & Environment Department, AIT-Austrian Institute of Technology, Molecular Diagnostics, Vienna, Austria; Oncotyrol, Center for Personalized Cancer Medicine, Innsbruck, Austria; Development Anti-Infectives Microbiology, Sandoz GmbH, Kundl, Austria
Reproduces experimentally determined qualitative dynamic behaviours and permits mechanistic analysis of genotype–phenotype relationships. QSSPN is a method integrating Petri nets and constraint-based analysis to predict the feasibility of qualitative dynamic behaviours in qualitative models of gene regulation, signaling and whole-cell metabolism. It includes regulatory mechanisms and a genome-scale metabolic network in human cell, using bile acid homeostasis in human hepatocytes as a case study.
A platform-independent, user-extensible MATLAB-based toolbox that provides an integrated computational environment to construct, manipulate and simulate glycans and their networks. It enables integration of XML-based glycan structure data into SBML (Systems Biology Markup Language) files that describe glycosylation reaction networks. Curation and manipulation of networks is facilitated using class definitions and glycomics database query tools. High quality visualization of networks and their steady-state and dynamic simulation are also supported.
A web tool for analyzing the topology of metabolic networks and calculating the set of exogenously acquired compounds. NetSeed is based on the seed detection algorithm, that allows for the quantification of an organism's metabolic dependence on its environment and enables the transformation of high-throughput genomic data into large-scale ecological data.
Uses the cellular metabolome to avoid the enumeration of thermodynamically infeasible elementary flux modes (EFMs). Specifically, given a metabolic network and a not necessarily complete metabolome, tEFMA efficiently returns the full set of thermodynamically feasible EFMs consistent with the metabolome. Compared to standard approaches tEFMA strongly reduces the memory consumption and the overall runtime. Thus tEFMA provides a new way to analyze unbiasedly hitherto inaccessible large-scale metabolic networks.
A tool for calculating the competitive potential between pairs of bacterial species. The score describes the effective metabolic overlap (EMO) between two species, derived from analyzing the topology of the corresponding metabolic models. NetCmpt is based on the EMO algorithm, developed and validated in previous studies. It takes as input lists of species-specific enzymatic reactions (EC numbers) and generates a matrix of the potential competition scores between all pairwise combinations.
Uses to view, edit, validate and annotate the simulation experiment description markup language (SED-ML) documents while shielding end-users from the underlying XML representation. SED-ED supports modellers who wish to create, understand and further develop a simulation description provided in SED-ML format. This tool provides a graphical editor to manipulate a workflow graph, in which nodes depict high-level SED-ML elements and edges the relations between them.
Allows creation and manipulation of SBML format metabolic networks with reactions and compounds defined as in the KEGG LIGAND database. MetNetMaker is an application that uses the KEGG LIGAND compound/reaction naming convention and provides a graphical interface dedicated to flux-balance analysis (FBA)-ready metabolic network creation. The software has two main tabs: (i) Reaction Creator to create custom reactions and add them to the reaction database and, (ii) Reaction Picker to browse the reaction database and select reactions using filters.
Computes reaction similarity based on the molecular signatures of participating molecules. RxnSim is able to compare reactions based on similarities of substrates and products in addition to their transformation. It allows masking of user-defined chemical moieties for weighted similarity computations.
An approach for the assignment of metabolic reactions (and as an extension, metagenomic sequence fragments annotated with metabolic genes) back to a parent metabolic network. We show that not only does SONEC aid in reconstructing species-level genomes, but it can also improve functional predictions made with the resulting metabolic networks.
Estimates partial correlation networks. The Correlation Calculator program implements the Debiased Sparse Partial Correlation algorithm (DSPC). It is a standalone Java application providing various methods of calculating pairwise correlations among repeatedly measured entities. It is designed for use with quantitative metabolite measurements such as mass spectrometry (MS) data on a set of samples. The workflow allows inspection and/or saving of results at various stages, and the final correlation results can be dynamically imported into MetScape as a correlation network.
Provides a plug-in for the Minecraft software to display metabolic networks. MetaboCraft produces 3D visualisations of metabolic network maps and individual metabolic pathways. This software exploits the sandbox building nature of the Minecraft game to provide an approach for dynamic and user-drive generation of structures representing arbitrary metabolic networks. It intends to be used for teaching biochemistry at secondary school or undergraduate levels.
Manages information related with metabolite identification. WebMetabase offers a platform that allows users to store, investigate and visualize data. The application provides modules to analyze specific or grouped compounds that includes features for kinetic, metabolic pathways or peptide frequency analysis as well as managing options to facilitate data sharing, import/export and reporting.
Enables the detection of regulated modules in metabolomics networks at different layers of resolution. MoDentify proposes a program that offers network inference, module identification, and interactive module visualization. It increases statistical power compared with classical association analysis and can be applied to any type of quantitative data due to its generic character.