BACKGROUND
plants are an increasingly facilitating and augmenting  human life and plant systems biology resources exist in a variety of locations
<cit> .
those researchers interested in a particular biological mechanism should be able to easily find and access all the data they need.
eliminating the need to go through the difficult process of shifting data from various databases from different platforms provides a strong incentive to create better, more integrated and easily accessible integrated plant portals.
a biological network database needs to capture and represent biological relationships in many ways.
metnet consists of a suite of software tools that specialize in different areas of systems biology
<cit> .
our database currently contains information about three plant species .
in the future we plan to also incorporate saccharomyces cerevisiae  and hypericum spp.
metnetdb is the underlying database and draws the majority of its information from external databases .
in addition to the retrieved information, a number of signal transduction pathways and biological entities have been manually curated with input from exper biologists.
metnet online features are compared with those of several other databases .
metnet is unique in a number of ways.
metnet online provides an easy-to-use front-end web interface and combines several important features to provide a distinctive platform.
first, metabolism, signalling, and transcriptional pathways are fully integrated into a single network.
second, a sub cellular location layer  overlays the pathways.
third, a protein-protein interaction layer extends pathway information.
fourth, the website allows for customized views of any data: .
fifth, metnet online has a “my metnet” component, which operates similarly to “my ncbi”.
users can keep track of  their favourite entities as well as lists of entities of particular interest .
user lists can be exported to other tools.
finally, the search function is sufficiently intelligent to recognize synonyms .
kegg
plantcyc
wikipathways
gramene
in order to enable users to easily analyse network data and customized content in metnet online, we provide different ways to export data  to facilitate data-flow to external applications.
for bioinformatics software developers, a separate application programming interface  is provided
<cit> .
metnet online is complementary to other community resources and provides a starting point for researchers to develop new hypotheses about biological function
<cit> .
implementation
metnetdb is a mysql database  that serves as the central repository for all metnet applications
<cit> .
metnetdb uses a labelled graph model to represent biological networks and complex internal relationships.
in this data model, an entity, which represents a biomolecule with a subcellular location, is mapped to a node in the labelled graph and all of its properties are assigned to the label of that node.
an interaction is also represented as a node in the model.
edges represent the relationship between an entity and an interaction.
the labelled graph model provides flexibility to integrate any types of biological data from any external source.
a complete list of data sources is available in table
<dig>
metnetdb provides a wide variety of data, including metabolic pathways, transcriptional regulatory networks, gene annotations, protein localization information, and metabolite annotations.
supplementary data may be added manually: curated pathway data is submitted after approval from researchers who are experts in their field, following the aracyc model of ‘expert users’.
in most cases, curated data is used to enrich the database with signal transduction interactions.
for arabidopsis, the best annotated of the networks, most of the metabolic pathways are imported from aracyc
<cit> .
regulatory information is obtained from agris
<cit> , a regulatory interaction database.
agris contains information on: binding site of promoters, loci of associated transcriptional factors, and corresponding references.
a full copy of gene ontology
<cit>  and tair gene annotations
<cit>  are incorporated.
metnetdb integrates mapman
<cit>  bin annotations, which have gene annotations and functional categories of the gene products.
in the future, information on regulons for arabidopsis genes
<cit> will be available, too.
metnetdb includes subcellular localization data from several sources.
when other information is unknown, locations are assigned from the protein sequences based on sequence similarity .
this method is superseded in metnetdb by experimental information, when available, from arabidopsis protein localization databases that collect data from a combination of experimentation, literature, and predictions.
specialized resources are used for particular organelles: ppdb
<cit> , plprot
<cit> , ampdb
<cit> , araperox
<cit> , and atnopdb
<cit> .
including .
ppdb  and plprot  contain plastid proteins of arabidopsis and other plants.
ampdb  contains arabidopsis mitochondrial protein data.
araperox  contains peroxisomal arabidopsis proteins.
atnopdb  contains arabidopsis nucleolar proteins.
metnetdb collects literature references from several sources.
aracyc and agris provide references for interactions.
chebi provides references for chemical compounds.
tair provides references for genes and corresponding rnas and proteins.
others references are input by curators.
our internal curator tool integrates with pathbinder
<cit>  to allow searching pubmed and adding selected biological references.
soybean data was inferred from microarray and sequence annotation with arabidopsis as a starting point for further curation.
based on arabidopsis network data, locus ids were converted to corresponding soybean  ids.
grapevine pathways were all manually constructed by field experts using celldesigner
<cit> .
a special plugin
<cit>  was subsequently used to transfer the data to metnetdb.
RESULTS
the metnet online portal
metnet online is a web application developed in php
<cit> .
graphviz  is used to generate graphical representations of pathways and networks .
biological entities and interactions are represented as nodes and the associations between them are represented as edges in the graph model.
the database serves as the primary data repository for both our online portal and the metnet suite of visualization and analysis tools
<cit> .
major features of the website are shown in figure
<dig>  a comparative list of features in relationship to select other online resources is available in table
<dig>
metnet online is centred on several concepts that are inherent in the underlying database.
entities represent physical molecules  and interactions can occur between any number of entities or between entities and other interactions .
a pathway is a collection of interactions that provides a convenient unit to represent prevailing cellular functions.
pathways in metnet are predefined and cannot be changed by a user, but can be integrated with each other or with other interactions to form new units.
a network in metnet is a collection of interactions for which the granularity is determined by the user when  he creates it.
a network can consist of any number of interactions or it can be a combination of some already defined pathways.
it can also map to exactly one pathway or it can map to a pathway minus transcription/translation events.
networks are virtual and transient objects.
the database can be browsed based on different ontologies or navigation trees including pathway category , entity participation, cellular location  and interaction type .
after navigating through a tree and selecting a node of interest, a list of pathways is displayed  and the pathway information screen can then be chosen or the pathway can be visualized directly.
visualization of a particular pathway may be different from what one is used to seeing at other locations or textbooks, as we rely on graphviz’s algorithms to render the underlying graphs: no manual intervention  is currently implemented in our data flow.
information about a pathway consists of general comments and literature references, location information, interactions contained within the pathway and participating entities.
sources and sinks for the pathway are displayed in a separate tab as part of the participating entities.
this is critical information for simulations in which the pathway is treated as a black box .
at the top-right of the pathway information screen, a toolbar is shown with export functions to various programs and a link to visualize the pathway .
entities can be browsed  independently of pathways and the entity information screen contains location information, possible synonyms, pathway participation and categorized interactions.
additional tabs are available on the pathway information screen.
the literature tab interfaces with pubmed to retrieve a current literature feed, in which the name of the pathway selected by the user is used as a search-term.
cellular context  is represented separately, so that one can get an idea of the various roles a protein or metabolite might play.
another tab shows connected pathways that share one or more entities.
metnet online visualizes pathways with their known or predicted sub cellular locations.
this information is not available anywhere else .
sub cellular location information can help scientists develop hypotheses on gene function.
entities are color-coded according to assigned location and shape-coded according to entity type.
interactions are color-coded according to type for easy identification and visualization.
metnet online’s search function is integrated, rather than providing different search functions for entities, interactions and pathways.
thus, search operations for “regulation”, “biosynthesis”, “at4g40090”, “agp3” or “malate” use the same interface.
search results are grouped by entity types, interactions and pathways.
when searching for “glucose”, for example, not only the “glucose” metabolite is presented but also the “glucose-udp biosynthesis” pathway, among others.
synonyms are taken into account.
searches for “h2o” and “water” or “o2” and “oxygen” both lead to the same entity.
typos and misspellings result in suggestions that often point a visitor in the right direction and when no results are found for a search, potential alternatives are suggested.
an example of this would be when “giberelin” is entered, the alternative “gibberellin” is proposed.
when visualizing a pathway, a graphviz  .dot file is generated and transformed into its visual representation .
in the upper left corner of the screen, a thumbnail of the complete pathway is shown to allow easy navigation through complex maps.
an indexed list of all participating entities is displayed underneath the thumbnail.
custom network design and personalization features
most pathway databases are static; in contrast, metnet online represents all lists of interactions and pathways with checkboxes in front of them.
a user can then choose either to visualize a pathway by itself or to select a set of pathways or interactions.
selection of any set pathways and/or interactions generates a new network by representing an integrated view of all selections .
due to computational and server restraints, we currently permit the user-generated network to consist of only up to  <dig> nodes.
the result is visualized using the methods discussed earlier or it can be exported as a whole to other tools.
any visitor can become a registered user of metnet online.
this opens up access to the “my metnet” function, which is implemented in a format that is similar to other personalization portals such as “my ncbi” or “my yahoo”.
when logged in, users gain access to additional functionality.
bookmarks can be used to efficiently retrieve objects of interest at any time in the future without having to navigate classification trees or execute a search.
entities, interactions and pathways can all be bookmarked, and bookmarked objects can have a commentary attached to them.
the “list of entities” is a second function in “my metnet”.
users can create and save multiple lists simultaneously.
lists can be created in three ways: a user can manually specify its members, convert a set of bookmarked entities into a list, or upload a text file.
an entity list can include experimental data, such as over-represented or under-represented genes from transcriptomics analysis or metabolites from a gc/ms experiment.
a list of entities, such as genes, or metabolites, can be forwarded to reactome’s skypainter function, to view an overlay of ‘omics data on the biological network
<cit> .
bird’s eye view , part of the metnet suite of applications and available through
http://www.metnetdb.org, is another tool that can be used for this
<cit> .
privacy issues are taken into consideration.
data related to these lists is stored in the metnetdb database, but is accessible only to the user that created it.
as a list gets longer, it is likely that additional pathways will be linked to the entities in that list.
in order to put results in perspective and to distinguish relevant from less relevant pathways, a separate interface contains the results of fisher’s exact test and ranks matching pathways by p-value .
fisher’s exact test is available for both visitors and registered users.
registered userscan automatically apply the fisher’s exact test to their stored customized lists of entities and interactions.
visitors have to specify their entities of interest manually in a text field.
while a user can extract and visualize data from the network in a wide variety of ways, no user can change anything in the original network without going through a metnet curator.
by providing the option to export pathways and subnetworks to other file formats, metnet online leverages existing software that incorporates a wide range of supplementary layout algorithms  in a more suitable environment than the web browser.
metnet online provides considerable connectivity for downstream data processing and it supports several export options including comma-separated values , sbml
<cit>  and xgmml.
sbml is sufficient to support most of the major features contained in the database and biopax can be used to encode < annotation > −elements in the output
<cit> .
as it becomes available, we plan to incorporate kinetic data in the sbml files .
xgmml is useful because it allows metnet online data to be transferred to cytoscape
<cit> .
use cases
a horticulturist who studies senescence is interested in ethylene metabolism and signalling
<cit> .
she wants to look at what is known about the process in the model plant, arabidopsis and visits the website and searches for the commonly used synonym,“ethene”.
metnet online recognizes the synonym and includes “ethylene” in the list of search results.
the user clicks on the link for the metabolite and sees three arabidopsis pathways that involve ethylene.
she selects all three and creates an integrated view.
although this is helpful in running additional analyses, she does not need the transcription and translation events.
she logs into her “my metnet” account and for easy access, she adds ethylene to her bookmarked entities.
using this shortcut, she visits the three ethylene-related pathways and examines the interactions contained in each pathway.
she then bookmarks the interactions that are of particular interest to her.
after doing so, she goes back to her bookmark overview page and sees a list of bookmarked interactions, all extracted from the various ethylene-related pathways.
she asks for a new integrated view of only these bookmarked interactions and she uses the scaling function in the visualization module to observe the entire network.
when she is satisfied, she clicks on the xgmml icon to export her custom network and transfers the data to cytoscape
<cit> , where she may examine additional properties of the network.
the result is shown in figure
<dig>  and the entire scenario is described in more detail in an online video tutorial at
http://www.metnetonline.org/tutorial.
in a second use case, a cell biologist has run a set of microarrays  on developing soybean embryos.
he identifies a list of differentially  expressed genes.
he saves the probe-names  as a separate text file  and visits the metnet online website.
he logs into his my metnet account and creates a personalized list by uploading the text file.
because the probe-names are recognized by metnet, he looks for pathways that are over-represented among the differentially expressed genes.
because numerous genes  are differentially expressed during embryo development, many pathways show up in an initial quantitative screen.
as such, the user decides to use the fisher exact test module to rank the pathway over-representation by p-value.
this presents him with useful information; the list of pathways is still large but they are now ranked by p-value for relevance.
he examines the pathways with the lowest p-values and is thus able to identify other potential gene targets for future experiments and verification.
the two use case scenarios for metnet are described in detail in an online video tutorial at
http://www.metnetonline.org/tutorial.
CONCLUSIONS
molecular biologists, physiologists and biotechnologists aim to understand the function of particular genes, polypeptides or metabolites, and to develop testable hypotheses as to how these biological entities function to influence the overall biological network.
easy and convenient access to integrated information from a variety of biological data repositories can greatly facilitate these goals.
we have built a new portal, metnet online, which provides a gateway to integrative systems biology applications.
the site generates simple pathways or complex representations of customized interaction sets or combined pathways.
in addition to existing data for arabidopsis, soybean and grapevine biological networks, metnet online incorporates manually curated interactions, in particular signal transduction interactions, and also introduces a sub cellular location data layer.
our site supplements other previously created tools, and interfaces with many of them.
users can integrate pathways and interactions to build custom network and track objects  that are of particular interest to them.
availability and requirements
the metnet online site can be reached at
http://www.metnetonline.org.
extensive video tutorials on how to use the site are available through
http://www.metnetonline.org/tutorial/.
competing interests
the author declare that they have no competing interests.
authors’ contributions
ys conceptualized and implemented the web portal, and prepared this manuscript.
yw was responsible for back-end data integration, data update, and data services.
jl established the initial schema for the database and developed curation tools.
esw is principal investigator of this project and supervised this manuscript.
all authors read and approved the final manuscript.
supplementary material
additional file 1
table s <dig>  comparing metnet online with other resources.
click here for file
acknowledgements
we thank all members of the metnet group for their valuable input and suggestions.
this material is based upon work supported by the following awards: national science foundation arabidopsis  <dig> # <dig>  and mcb- <dig>  and eec- <dig>  and by a plant sciences institute award .

 plants are an increasingly facilitating and augmenting human life and plant systems biology resources exist in a variety of locations. those researchers interested in a particular biological mechanism should be able to easily find and access all the data they need. eliminating the need to go through the difficult process of shifting data from various databases from different platforms provides a strong incentive to create better, more integrated and easily accessible integrated plant portals. a biological network database needs to capture and represent biological relationships in many ways. metnet consists of a suite of software tools that specialize in different areas of systems biology. our database currently contains information about three plant species. in the future we plan to also incorporate saccharomyces cerevisiae and hypericum spp. metnetdb is the underlying database and draws the majority of its information from external databases. in addition to the retrieved information, a number of signal transduction pathways and biological entities have been manually curated with input from exper biologists. metnet online features are compared with those of several other databases. metnet is unique in a number of ways. metnet online provides an easy-to-use front-end web interface and combines several important features to provide a distinctive platform. first, metabolism, signalling, and transcriptional pathways are fully integrated into a single network. second, a sub cellular location layer overlays the pathways. third, a protein-protein interaction layer extends pathway information. fourth, the website allows for customized views of any data:. fifth, metnet online has a “my metnet” component, which operates similarly to “my ncbi”. users can keep track of their favourite entities as well as lists of entities of particular interest. user lists can be exported to other tools. finally, the search function is sufficiently intelligent to recognize synonyms. kegg plantcyc wikipathways gramene in order to enable users to easily analyse network data and customized content in metnet online, we provide different ways to export data to facilitate data-flow to external applications. for bioinformatics software developers, a separate application programming interface is provided. metnet online is complementary to other community resources and provides a starting point for researchers to develop new hypotheses about biological function. implementation metnetdb is a mysql database that serves as the central repository for all metnet applications. metnetdb uses a labelled graph model to represent biological networks and complex internal relationships. in this data model, an entity, which represents a biomolecule with a subcellular location, is mapped to a node in the labelled graph and all of its properties are assigned to the label of that node. an interaction is also represented as a node in the model. edges represent the relationship between an entity and an interaction. the labelled graph model provides flexibility to integrate any types of biological data from any external source. a complete list of data sources is available in table metnetdb provides a wide variety of data, including metabolic pathways, transcriptional regulatory networks, gene annotations, protein localization information, and metabolite annotations. supplementary data may be added manually: curated pathway data is submitted after approval from researchers who are experts in their field, following the aracyc model of ‘expert users’. in most cases, curated data is used to enrich the database with signal transduction interactions. for arabidopsis, the best annotated of the networks, most of the metabolic pathways are imported from aracyc. regulatory information is obtained from agris, a regulatory interaction database. agris contains information on: binding site of promoters, loci of associated transcriptional factors, and corresponding references. a full copy of gene ontology and tair gene annotations are incorporated. metnetdb integrates mapman bin annotations, which have gene annotations and functional categories of the gene products. in the future, information on regulons for arabidopsis genes will be available, too. metnetdb includes subcellular localization data from several sources. when other information is unknown, locations are assigned from the protein sequences based on sequence similarity. this method is superseded in metnetdb by experimental information, when available, from arabidopsis protein localization databases that collect data from a combination of experimentation, literature, and predictions. specialized resources are used for particular organelles: ppdb, plprot, ampdb, araperox, and atnopdb. including. ppdb and plprot contain plastid proteins of arabidopsis and other plants. ampdb contains arabidopsis mitochondrial protein data. araperox contains peroxisomal arabidopsis proteins. atnopdb contains arabidopsis nucleolar proteins. metnetdb collects literature references from several sources. aracyc and agris provide references for interactions. chebi provides references for chemical compounds. tair provides references for genes and corresponding rnas and proteins. others references are input by curators. our internal curator tool integrates with pathbinder to allow searching pubmed and adding selected biological references. soybean data was inferred from microarray and sequence annotation with arabidopsis as a starting point for further curation. based on arabidopsis network data, locus ids were converted to corresponding soybean ids. grapevine pathways were all manually constructed by field experts using celldesigner. a special plugin was subsequently used to transfer the data to metnetdb.  the metnet online portal metnet online is a web application developed in php. graphviz is used to generate graphical representations of pathways and networks. biological entities and interactions are represented as nodes and the associations between them are represented as edges in the graph model. the database serves as the primary data repository for both our online portal and the metnet suite of visualization and analysis tools. major features of the website are shown in figure a comparative list of features in relationship to select other online resources is available in table metnet online is centred on several concepts that are inherent in the underlying database. entities represent physical molecules and interactions can occur between any number of entities or between entities and other interactions. a pathway is a collection of interactions that provides a convenient unit to represent prevailing cellular functions. pathways in metnet are predefined and cannot be changed by a user, but can be integrated with each other or with other interactions to form new units. a network in metnet is a collection of interactions for which the granularity is determined by the user when he creates it. a network can consist of any number of interactions or it can be a combination of some already defined pathways. it can also map to exactly one pathway or it can map to a pathway minus transcription/translation events. networks are virtual and transient objects. the database can be browsed based on different ontologies or navigation trees including pathway category, entity participation, cellular location and interaction type. after navigating through a tree and selecting a node of interest, a list of pathways is displayed and the pathway information screen can then be chosen or the pathway can be visualized directly. visualization of a particular pathway may be different from what one is used to seeing at other locations or textbooks, as we rely on graphviz’s algorithms to render the underlying graphs: no manual intervention is currently implemented in our data flow. information about a pathway consists of general comments and literature references, location information, interactions contained within the pathway and participating entities. sources and sinks for the pathway are displayed in a separate tab as part of the participating entities. this is critical information for simulations in which the pathway is treated as a black box. at the top-right of the pathway information screen, a toolbar is shown with export functions to various programs and a link to visualize the pathway. entities can be browsed independently of pathways and the entity information screen contains location information, possible synonyms, pathway participation and categorized interactions. additional tabs are available on the pathway information screen. the literature tab interfaces with pubmed to retrieve a current literature feed, in which the name of the pathway selected by the user is used as a search-term. cellular context is represented separately, so that one can get an idea of the various roles a protein or metabolite might play. another tab shows connected pathways that share one or more entities. metnet online visualizes pathways with their known or predicted sub cellular locations. this information is not available anywhere else. sub cellular location information can help scientists develop hypotheses on gene function. entities are color-coded according to assigned location and shape-coded according to entity type. interactions are color-coded according to type for easy identification and visualization. metnet online’s search function is integrated, rather than providing different search functions for entities, interactions and pathways. thus, search operations for “regulation”, “biosynthesis”, “at4g40090”, “agp3” or “malate” use the same interface. search results are grouped by entity types, interactions and pathways. when searching for “glucose”, for example, not only the “glucose” metabolite is presented but also the “glucose-udp biosynthesis” pathway, among others. synonyms are taken into account. searches for “h2o” and “water” or “o2” and “oxygen” both lead to the same entity. typos and misspellings result in suggestions that often point a visitor in the right direction and when no results are found for a search, potential alternatives are suggested. an example of this would be when “giberelin” is entered, the alternative “gibberellin” is proposed. when visualizing a pathway, a graphviz.dot file is generated and transformed into its visual representation. in the upper left corner of the screen, a thumbnail of the complete pathway is shown to allow easy navigation through complex maps. an indexed list of all participating entities is displayed underneath the thumbnail. custom network design and personalization features most pathway databases are static; in contrast, metnet online represents all lists of interactions and pathways with checkboxes in front of them. a user can then choose either to visualize a pathway by itself or to select a set of pathways or interactions. selection of any set pathways and/or interactions generates a new network by representing an integrated view of all selections. due to computational and server restraints, we currently permit the user-generated network to consist of only up to nodes. the result is visualized using the methods discussed earlier or it can be exported as a whole to other tools. any visitor can become a registered user of metnet online. this opens up access to the “my metnet” function, which is implemented in a format that is similar to other personalization portals such as “my ncbi” or “my yahoo”. when logged in, users gain access to additional functionality. bookmarks can be used to efficiently retrieve objects of interest at any time in the future without having to navigate classification trees or execute a search. entities, interactions and pathways can all be bookmarked, and bookmarked objects can have a commentary attached to them. the “list of entities” is a second function in “my metnet”. users can create and save multiple lists simultaneously. lists can be created in three ways: a user can manually specify its members, convert a set of bookmarked entities into a list, or upload a text file. an entity list can include experimental data, such as over-represented or under-represented genes from transcriptomics analysis or metabolites from a gc/ms experiment. a list of entities, such as genes, or metabolites, can be forwarded to reactome’s skypainter function, to view an overlay of ‘omics data on the biological network. bird’s eye view, part of the metnet suite of applications and available through http://www.metnetdb.org, is another tool that can be used for this. privacy issues are taken into consideration. data related to these lists is stored in the metnetdb database, but is accessible only to the user that created it. as a list gets longer, it is likely that additional pathways will be linked to the entities in that list. in order to put results in perspective and to distinguish relevant from less relevant pathways, a separate interface contains the results of fisher’s exact test and ranks matching pathways by p-value. fisher’s exact test is available for both visitors and registered users. registered userscan automatically apply the fisher’s exact test to their stored customized lists of entities and interactions. visitors have to specify their entities of interest manually in a text field. while a user can extract and visualize data from the network in a wide variety of ways, no user can change anything in the original network without going through a metnet curator. by providing the option to export pathways and subnetworks to other file formats, metnet online leverages existing software that incorporates a wide range of supplementary layout algorithms in a more suitable environment than the web browser. metnet online provides considerable connectivity for downstream data processing and it supports several export options including comma-separated values, sbml and xgmml. sbml is sufficient to support most of the major features contained in the database and biopax can be used to encode < annotation > −elements in the output. as it becomes available, we plan to incorporate kinetic data in the sbml files. xgmml is useful because it allows metnet online data to be transferred to cytoscape. use cases a horticulturist who studies senescence is interested in ethylene metabolism and signalling. she wants to look at what is known about the process in the model plant, arabidopsis and visits the website and searches for the commonly used synonym,“ethene”. metnet online recognizes the synonym and includes “ethylene” in the list of search results. the user clicks on the link for the metabolite and sees three arabidopsis pathways that involve ethylene. she selects all three and creates an integrated view. although this is helpful in running additional analyses, she does not need the transcription and translation events. she logs into her “my metnet” account and for easy access, she adds ethylene to her bookmarked entities. using this shortcut, she visits the three ethylene-related pathways and examines the interactions contained in each pathway. she then bookmarks the interactions that are of particular interest to her. after doing so, she goes back to her bookmark overview page and sees a list of bookmarked interactions, all extracted from the various ethylene-related pathways. she asks for a new integrated view of only these bookmarked interactions and she uses the scaling function in the visualization module to observe the entire network. when she is satisfied, she clicks on the xgmml icon to export her custom network and transfers the data to cytoscape, where she may examine additional properties of the network. the result is shown in figure and the entire scenario is described in more detail in an online video tutorial at http://www.metnetonline.org/tutorial. in a second use case, a cell biologist has run a set of microarrays on developing soybean embryos. he identifies a list of differentially expressed genes. he saves the probe-names as a separate text file and visits the metnet online website. he logs into his my metnet account and creates a personalized list by uploading the text file. because the probe-names are recognized by metnet, he looks for pathways that are over-represented among the differentially expressed genes. because numerous genes are differentially expressed during embryo development, many pathways show up in an initial quantitative screen. as such, the user decides to use the fisher exact test module to rank the pathway over-representation by p-value. this presents him with useful information; the list of pathways is still large but they are now ranked by p-value for relevance. he examines the pathways with the lowest p-values and is thus able to identify other potential gene targets for future experiments and verification. the two use case scenarios for metnet are described in detail in an online video tutorial at http://www.metnetonline.org/tutorial.  molecular biologists, physiologists and biotechnologists aim to understand the function of particular genes, polypeptides or metabolites, and to develop testable hypotheses as to how these biological entities function to influence the overall biological network. easy and convenient access to integrated information from a variety of biological data repositories can greatly facilitate these goals. we have built a new portal, metnet online, which provides a gateway to integrative systems biology applications. the site generates simple pathways or complex representations of customized interaction sets or combined pathways. in addition to existing data for arabidopsis, soybean and grapevine biological networks, metnet online incorporates manually curated interactions, in particular signal transduction interactions, and also introduces a sub cellular location data layer. our site supplements other previously created tools, and interfaces with many of them. users can integrate pathways and interactions to build custom network and track objects that are of particular interest to them. availability and requirements the metnet online site can be reached at http://www.metnetonline.org. extensive video tutorials on how to use the site are available through http://www.metnetonline.org/tutorial/. competing interests the author declare that they have no competing interests. authors’ contributions ys conceptualized and implemented the web portal, and prepared this manuscript. yw was responsible for back-end data integration, data update, and data services. jl established the initial schema for the database and developed curation tools. esw is principal investigator of this project and supervised this manuscript. all authors read and approved the final manuscript. supplementary material additional file 1 table s comparing metnet online with other resources. click here for file acknowledgements we thank all members of the metnet group for their valuable input and suggestions. this material is based upon work supported by the following awards: national science foundation arabidopsis # and mcb- and eec- and by a plant sciences institute award.
metnet online is a web-based portal that provides access to a regulatory and metabolic plant pathway database. metnet online enables pathways, interactions and entities to be browsed or searched by multiple categories such as sub cellular compartment, pathway ontology, and go term. the study of plant biological pathways is advanced by easy access to integrated data sources. today, various plant data sources are scattered throughout the web, making it increasingly complicated to build comprehensive datasets. extensive video tutorials on how to use the site are available through
 plants are important as foods, pharmaceuticals, biorenewable chemicals, fuel resources, bioremediation tools and general tools for recombinant technology. the study of plant biological pathways is advanced by easy access to integrated data sources. today, various plant data sources are scattered throughout the web, making it increasingly complicated to build comprehensive datasets.  metnet online is a web-based portal that provides access to a regulatory and metabolic plant pathway database. the database and portal integrate arabidopsis, soybean and grapevine data. pathways are enriched with known or predicted information on sub cellular location. metnet online enables pathways, interactions and entities to be browsed or searched by multiple categories such as sub cellular compartment, pathway ontology, and go term. in addition to this, the “my metnet” feature allows registered users to bookmark content and track, import and export customized lists of entities. users can also construct custom networks using existing pathways and/or interactions as building blocks.  the site can be reached at http://www.metnetonline.org. extensive video tutorials on how to use the site are available through http://www.metnetonline.org/tutorial/. 