DSP: Storage > Processing > Statistics > Identification > Interpretation
Biological interpretation
How do you interpret you metabolomics data?
Understanding the meaning of changes in metabolites is not easy. Metabolism is highly connected and a change in a certain metabolite can be caused by changes in many pathways. Therefore understanding the relation between metabolites is essential. For this purpose you can either use pathways tools or modeling tools. Pathways tools will show the connections, whereas modeling tools can also help you understand the dynamic changes. See also the NuGO website for more details on nutritional studies (http://www.nugo.org/metabolomics).
Interpretation database
Name: Hora suite
Location:http://www.paternostrolab.org/
Description: HORA suite (Human blOod Range vAlidator) is a Java application developed to validate the metabolomic analysis of human blood. It bases the search work on a database, built in our laboratory that stores the normal plasma and serum range concentrations of metabolites.
Name: NuGOwiki
Location: http://www.nugowiki.org/
Description: Metabolomics has now been for several years a method that has been developed and used by analytical chemists. Therefore, many metabolite databases are highly chemically directed. NuGOwiki is a site that contains biological information on metabolites. Input on this information given by any registered user and the history of adjustments can be retrieved.
Biological pathways analysis tools
Name: Pathvisio
Location: http://www.pathvisio.org/
Description: PathVisio is a pathway visualization and editing program using pathways in the GPML format. It is meant to be flexible enough to display many different types of data, such as microarray data and proteomics data, on familiar biological pathways. The available GPML pathways are converted directly from GenMAPP pathways, and should appear exactly the same.
Name: Ingenuity
Location: http://www.ingenuity.com/products/pathways_analysis.html
Description: Ingenuity Pathways Analysis (IPA) is an all-in-one software application that enables researchers to model, analyze, and understand the complex biological and chemical systems at the core of life science research. IPA has been broadly adopted by the life sciences research community and cited in hundreds of peer-reviewed journal articles.
Name: Metacore
Location: http://www.genego.com/metacore.php
Description: MetaCore™ is an integrated software suite for functional analysis of experimental data. The scope of data types includes microarray and SAGE gene expression, SNPs and CGH arrays, proteomics, metabolomics, pathway analysis, Y2H and other custom interactions. MetaCore™ is based on a proprietary manually curated database of human protein-protein, protein-DNA and protein compound interactions, metabolic and signaling pathways and the effects of bioactive molecules in gene expression. The analytical package includes easy to use, intuitive tools for data visualization, mapping and exchange, multiple networking algorithms and filters.
Name: Pathway Hunter
Location: http://pht.tu-bs.de/PHT/
Description: Pathway Hunter Tool (PHT) is a robust and user friendly Systems Biology-based BioInformatics tool to process biologically relevant information. The tool finds all the valid bio-chemical shortest paths that connect two molecules in selected organisms. Further it generates a list of potential drug targets for the selected genomes based on the production/consumption load on metabolites or enzymes. This requires further in vitro/ in vivo verification. The tool presents overall connectivity information for the selected organisms.
Name: VANTED
Location: http://vanted.ipk-gatersleben.de/
Description: This system makes it possible to load and edit graphs, which may represent biological pathways or functional hierarchies. It is possible to map experimental datasets onto the graph elements and visualize time series data or data of different genotypes or environmental conditions in the context of a the underlying biological processes. Built-in statistic functions allow a fast evaluation of the data (e.g. t-Test or correlation analysis).
Modeling tools
Name: JWS online
Location: http://jjj.biochem.sun.ac.za/
Description: JWS Online is a Systems Biology tool for simulation of kinetic models from a curated model database. Click on the Model Database tab to access the models, or on the other tabs for more information.
Name: Biomodels
Location: http://www.ebi.ac.uk/biomodels/
Description: BioModels Database is a data resource that allows biologists to store, search and retrieve published mathematical models of biological interests. Models present in BioModels Database are annotated and linked to relevant data resources, such as publications, databases of compounds and pathways, controlled vocabularies, etc.
Name: COPASI: Complex Pathway Simulator
Location: http://www.copasi.org/tiki-index.php
Description: COPASI is a software application for simulation and analysis of biochemical networks.
Name: SimBiology
Location: http://www.mathworks.com/products/simbiology/
Description: SimBiology® extends MATLAB® with tools for modeling, simulating, and analyzing biochemical pathways. You can create your own block diagram model using predefined blocks. You can manually enter in compartments, species, parameters, reactions, events, rules, kinetic laws, and units, or read in Systems Biology Mark-Up Language (SBML) models. SimBiology software lets you simulate a model using stochastic or deterministic solvers and analyze your pathway with tools such as parameter estimation and sensitivity analysis. A graphical user interface (GUI) provides access to command-line functionality and lets you create and manage compartments, reactions, events, species, parameters, rules, and units.
Name: ByoDyn
Location: http://cbbl.imim.es:8080/ByoDyn
Description: ByoDyn has been designed to provide an easily extendable computational framework to estimate and analyze parameters in highly uncharacterized models.ByoDyn includes a set of tools to 1) integrate ordinary differential equations (ODEs), including systems with events, rules (differential algebraic equations, DAE) and delays built from a given biological model; 2) globally optimize the parameters that fit the provided experimental information and evaluate the sensitivity of the model with respect to the different parameters; and 3) include the sensitivity of the parameters in an optimal experimental design pipeline. The program makes use of external software, providing a Python binding schema that allows the user to easily implement new software in the desired calculation protocol. The program benefits from its interface with the SBML library, which ensures communication with other existing tools in the field.
Name: CellDesigner
Location: http://www.systems-biology.org/cd/
Description: CellDesigner is a structured diagram editor for drawing gene-regulatory and biochemical networks. Networks are drawn based on the process diagram, with graphical notation system proposed by Kitano, and are stored using the Systems Biology Markup Language (SBML), a standard for representing models of biochemical and gene-regulatory networks. Networks are able to link with simulation and other analysis packages through Systems Biology Workbench (SBW).
Name: Cytoscape
Location: http://www.cytoscape.org/
Description: Cytoscape is an open source bioinformatics software platform for visualizing molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data. Although Cytoscape was originally designed for biological research, now it is a general platform for complex network analysis and visualization. Cytoscape core distribution provides a basic set of features for data integration and visualization. Additional features are available as plugins. Plugins are available for network and molecular profiling analyses, new layouts, additional file format support, scripting, and connection with databases. Plugins may be developed by anyone using the Cytoscape open API based on Java technology and plugin community development is encouraged. Most of the plugins are freely available.
Sources of biological pathways
Name: ExPASy
Location: http://www.expasy.ch/cgi-bin/search-biochem-index
Description: This page gives access to the digitized version of the Roche Applied Science "Biochemical Pathways" wall chart.
Name: Wikipathways
Location: http://www.wikipathways.org
Description: Wikipathways is a online pathway database.
Name: KEGG: Kyoto Encyclopedia of Genes and Genomes
Location: http://www.genome.jp/kegg/
Description: The goal of this website is to build a bioinformatics resource as complete computer representation of the cell, the organism, and the biosphere, which will enable computational prediction of higher-level complexity of cellular processes and organism behaviors from genomic and molecular information. For metabolites especially http://www.genome.ad.jp/kegg/ligand.html, which includes possibilities to search for chemical formula, name, exact mass, and pathway.
Name: Sigma Aldrich clickable metabolic pathway map
Location: http://www.sigmaaldrich.com/img/assets/4202/MetabolicPathways_6_17_04_.pdf
Name: Nicholson minimaps
Location: http://www.sigmaaldrich.com/Area_of_Interest/Life_Science/Metabolomics/K...
Nicholson minimaps give an overview of major individual metabolic pathways.
Name: Metacyc
Location: http://metacyc.org/
Metacyc is a database of nonredundant, experimentally elucidated metabolic pathways (<300 organisms).
Name: Reactome
Location: http://www.reactome.org/
The Reactome project is a collaboration among Cold Spring Harbor Laboratory, The European Bioinformatics Institute, and The Gene Ontology Consortium to develop a curated resource of core pathways and reactions in human biology. The information in this database is authored by biological researchers with expertise in their fields, maintained by the Reactome editorial staff, and cross-referenced with the sequence databases at NCBI, Ensembl and UniProt, the UCSC Genome Browser , HapMap, KEGG(Gene and Compound ), ChEBI, PubMed and GO. In addition to curated human events, inferred orthologous events in 22 non-human species including mouse, rat, chicken, puffer fish, worm, fly, yeast, two plants and E.coli are also available. A description of Reactome has been published in Genome Biology genomebiology.com/2007/8/3/r39.