Sources of biological pathways
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.
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.
Freeware Advantages: easy to create your own pathways and visualize your experimental data. Possibilities to add literature references to the links drawn. Good tutorials are available on the website. Visualization of different datatypes in one pathway is possible (i.e. metabolite data and gene data). Metabolite data can be uploaded by HMDB code and CAS number. Pathways can eventually be uploaded in wikipathways to make them publicly available (www.wikipathways.org).
Drawbacks: No possibilities to upload data on the level of enzymes (i.e. EC numbers). No possibilities to combine information available in the pathways into biological networks. No biological descriptions available for metabolites.
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.
Commercial Advantages: straightforward and user friendly pathway visualization and analysis tool. Extensive help files are available. Metabolomics data can be uploaded as KEGG and PubChem ID. Every metabolite has its own ‘chem view’ page, summarizing chemical information, but also biological information such as ‘what does the metabolite regulate’, ‘by what is the metabolite regulated’, ‘what is its role in the cell’, ‘what does it bind’, and ‘what diseases are associated with the metabolite’. This biological information is created by textmining tools. References and citations of the information behind these biological associations are easily accessible. The tool creates on the basis of the textmining information and pathways biological networks of your uploaded metabolites (on the basis of the default algorithm ‘shortest path’).
Drawbacks: the information gathered by textmining tools are not manually curated by IPA, so you need to this by yourself and therefore be very careful in the interpretation of your results! There are no possibilities to visualize and analyze different datatypes (i.e. metabolite data combined with transcriptomics data). No possibilities to visualize & analyze your data on the level of biofluids such as blood and/or urine. Not species specific. No possibilities to edit own pathways or networks.
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.
Commercial, access available through NuGO ()Advantages: A nice pathway analysis and visualization tool. Good tutorials are available and there is a monthly online webex meeting in which Genego leads you through the Metacore software package. Metacore recognizes the following metabolite ID’s: chemical name, Brutto Formula, Molecular Weight, SMILES, InChI, CAS Number, KeGG ID, PubChem Compound ID, GeneGo Compound ID. For metabolomics, especially the biological network algorithms are interesting, which makes it easy to mine your data in a biological context. References behind biological links are easily accessible. It is possible to visualize mouse, rat, worm, fly, yeast and dog data on maps and networks. Moreover you can mine your data in real time: multiple data points, conditions, time-series, treatments can be visualized through animated videos. Finally you can apply disease, tissue, functional processes and sub-cellular localization filters to focus networks on information that is relevant to your study. It is possible to visualize different datatypes (i.e. metabolite and genedata).
Drawbacks: No possibilities to visualize & analyze your data on the level of biofluids such as blood and/or urine. There are possibilities to edit and create your own pathways, however you need an extension of your license with MapEditor software. Statistical algorithms available to calculate which pathways are enriched are not suitable for metabolomics data (it assumes that all metabolites available in the database are measured and quantified). No biological descriptions available for metabolites.
Name: Pathway HunterLocation: 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.
Freeware
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).
Shareware
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.
Freeware
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.
Freeware
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.
Shareware
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.
Commercial
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.
Freeware
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).
Freeware
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.
Freeware
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 mapLocation: 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/Key_Resources/Metabolic_Pathways/IUBMB_Nicholson_Minimaps.html
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.
Reference: Ma, H. W. & Goryanin, I. (2008) Human metabolic network reconstruction and its impact on drug discovery and development. Drug Discov Today, 13: 402-408
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.
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.
Freeware Advantages: easy to create your own pathways and visualize your experimental data. Possibilities to add literature references to the links drawn. Good tutorials are available on the website. Visualization of different datatypes in one pathway is possible (i.e. metabolite data and gene data). Metabolite data can be uploaded by HMDB code and CAS number. Pathways can eventually be uploaded in wikipathways to make them publicly available (www.wikipathways.org).
Drawbacks: No possibilities to upload data on the level of enzymes (i.e. EC numbers). No possibilities to combine information available in the pathways into biological networks. No biological descriptions available for metabolites.
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.
Commercial Advantages: straightforward and user friendly pathway visualization and analysis tool. Extensive help files are available. Metabolomics data can be uploaded as KEGG and PubChem ID. Every metabolite has its own ‘chem view’ page, summarizing chemical information, but also biological information such as ‘what does the metabolite regulate’, ‘by what is the metabolite regulated’, ‘what is its role in the cell’, ‘what does it bind’, and ‘what diseases are associated with the metabolite’. This biological information is created by textmining tools. References and citations of the information behind these biological associations are easily accessible. The tool creates on the basis of the textmining information and pathways biological networks of your uploaded metabolites (on the basis of the default algorithm ‘shortest path’).
Drawbacks: the information gathered by textmining tools are not manually curated by IPA, so you need to this by yourself and therefore be very careful in the interpretation of your results! There are no possibilities to visualize and analyze different datatypes (i.e. metabolite data combined with transcriptomics data). No possibilities to visualize & analyze your data on the level of biofluids such as blood and/or urine. Not species specific. No possibilities to edit own pathways or networks.
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.
Commercial, access available through NuGO ()Advantages: A nice pathway analysis and visualization tool. Good tutorials are available and there is a monthly online webex meeting in which Genego leads you through the Metacore software package. Metacore recognizes the following metabolite ID’s: chemical name, Brutto Formula, Molecular Weight, SMILES, InChI, CAS Number, KeGG ID, PubChem Compound ID, GeneGo Compound ID. For metabolomics, especially the biological network algorithms are interesting, which makes it easy to mine your data in a biological context. References behind biological links are easily accessible. It is possible to visualize mouse, rat, worm, fly, yeast and dog data on maps and networks. Moreover you can mine your data in real time: multiple data points, conditions, time-series, treatments can be visualized through animated videos. Finally you can apply disease, tissue, functional processes and sub-cellular localization filters to focus networks on information that is relevant to your study. It is possible to visualize different datatypes (i.e. metabolite and genedata).
Drawbacks: No possibilities to visualize & analyze your data on the level of biofluids such as blood and/or urine. There are possibilities to edit and create your own pathways, however you need an extension of your license with MapEditor software. Statistical algorithms available to calculate which pathways are enriched are not suitable for metabolomics data (it assumes that all metabolites available in the database are measured and quantified). No biological descriptions available for metabolites.
Name: Pathway HunterLocation: 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.
Freeware
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).
Shareware
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.
Freeware
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.
Freeware
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.
Shareware
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.
Commercial
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.
Freeware
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).
Freeware
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.
Freeware
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 mapLocation: 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/Key_Resources/Metabolic_Pathways/IUBMB_Nicholson_Minimaps.html
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.
Reference: Ma, H. W. & Goryanin, I. (2008) Human metabolic network reconstruction and its impact on drug discovery and development. Drug Discov Today, 13: 402-408
Labels:
bioinformatics
