post - genomic biology makes extensive use of network analysis at all levels of the hierarchy of life .
networks are basic tools in systems biology for expressing the essence of living things as whole integrated systems [ 1 - 3 ] .
the explosive development of the theory of dynamic evolutionary networks during the past decade[4 - 6 ] stimulated the creation of numerous algorithms and software programs for constructing , manipulating and analysing networks .
many of those are multi - purpose programs with applications to most of the available types of complex networks : social , transportation , communication , financial , etc .
this review focuses on software for the analysis of networks in living cells , the nodes in which represent genes , proteins , metabolites and other cell components .
examples of such networks are protein - protein interaction networks ( ppn ) , gene regulatory networks ( grn ) , and metabolic and signalling networks and pathways , as well as disease - related or cell function - related networks .
the detailed analysis in this review is devoted to several of the most comprehensive and multi - functional software packages for network analysis in molecular biology .
other essential types of software in this field , which solve more specific network tasks , are also listed .
one such kind of software performs a substructure search for identifying over - represented sub - graphs called motifs .
viewed as the smallest building blocks of networks , motifs serve as a signature for distinguishing species , or different states of a single species , and are of interest for evolutionary and biomedical studies .
the concept of motifs was developed in the laboratory of uri alon from the weizmann institute in israel , where a library of identification ( i d ) numbers of all motifs having three to eight nodes was created , along with the downloadable mfinder software for motif identification .
other groups followed with freely available software : mavisto ( schreiber and schwbbermeyer ) and fanmod ( wernicke and rasche ) .
fanmod is particularly user - friendly and fast software which runs under linux , macos and windows , and classifies the motifs according to their frequency of distribution , p values and z - scores , in comparison with the generated randomised networks having the same size and the same node degree distribution .
recently , another freely available software , named kavosh ( kashani et al . ) ,   claimed slightly better performance than fanmod and added the option of handling motifs having more than eight nodes .
modularisation of networks is another area of intensive research , aimed at facilitating the analysis of complex networks by partitioning them into modules , presumably related to a certain biological function .
a large variety of approaches have been proposed , many of them constructing different network profiles and hierarchical trees , such as those based on node connectivity ( the topological overlap method of ravasz et al . ) and node distance ( the association matrix method of rives and galitski ) .
another group of methods includes extreme pathway analysis ( papin et al . ) and flux analysis ( burgard et al . ) in metabolic networks .
the simulated annealing algorithm ( guimer and nunes amaral ) is a stochastic optimisation technique that enables the discovery of low computational cost modular configurations without getting trapped in ' high - cost ' local minima .
the optimised modularisation function is based on accounting for the fractions of intra - module and inter - module links .
the first algorithm of newman makes use of a similar type of modularisation function and agglomerative hierarchical clustering procedure .
the newman 2006 algorithm uses a modularity score defined in terms of the eigenvectors and eigenvalues of a specifically defined modularity matrix .
the algorithm is very fast : a network with 27,000 nodes runs for 20 minutes on a standard personal computer .
both software programs are available from the author on request . a third , more recent , group of network - related software provides tools for direct network comparison .
software of this type aims to prove that comparative interactomics can reproduce the results provided by comparative genomics and , in addition , can identify conserved functional modules , predict network module functions and query such modules .
the basic software is the network comparison toolkit ( nct ) , a java 1.5 library developed to be modular , easily extended and freely downloadable .
the project was initiated in the ideker laboratory at the university of california , san diego ( ucsd ) .
stanford university developed graemlin , another software package for network comparison , which provides fast network alignment that scales linearly with the number of networks compared , and supports efficient querying of modules .
the software scores separate species into equivalence classes and reconstructs the most parsimonious ancestral history of an equivalence class using dynamic programming based on five types of evolutionary events .
graemlin 2.0 is freely available and the source code is available under the gnu public licence .
( ' gnu ' is an acronym for ' gnu 's not unixi ' and is a unix - like computer operating system , composed of free software . )
pathway studio ( ariadne genomics , rockville , md ) is a software which builds networks and pathways from relationships between biological molecules and processes extracted from the literature , pubmed , databases , expression and proteomics data .
pathway studio is offered with the resnet mammalian and resnet plant databases , and supports kegg , science signaling and prolexys hynet protein - protein interaction databases .
the resnet 7.0 database contains over 1.5 million relationships for 110,435 proteins , 814 cellular processes , 2,410 diseases and 248 curated pathways .
the resnet plant database includes over 90,000 relationships for 71,501 proteins , 915 cellular processes , 97 plant diseases , and 315 aracyc and 17 plant signalling pathways .
the software also calculates the node degrees in the network built , and compares them with the node degrees in the resnet database .
pathway studio enterprise includes server - side applications with windows , linux and solaris , compared with the client - side windows ( xp , vista and 7 ) applications of the desktop version .
the desktop version of pathway studio 7.0 requires a minimum of 2 gb ram , while 4 gb are recommended .
the server makes use of two or more quad - core intel / amd processors with 4 - 10 gb ram and 32-/64-bit operating system ( os ) and java virtual machine ( jvm ) -- a crucial component of the java platform .
a java - based start - up application downloads to your machine and initiates the connection to ingenuity systems back - end server infrastructure .
this allows ipa to be run on any machine with a web interface running most versions of windows , from xp to 7 , and max os 10.4.2 to 10.6.2 .
the most recent ipa 8.0 version requires a minimum of 512 mb of ram but recommends 1 gb for windows xp and mac os x , and 2 gb under vista and windows 7 .
ipa uses a database for human genes / proteins , created from manually curated literature searches ( ingenuityexpertassist findings ) .
specific data on the number of interactions and the number of molecules is not reported .
ipa also includes interaction data from third party databases , such as intact , bind , dip , mint , mips , biogrid and cognia .
the core analysis is the basic block for analysis of protein - protein interaction networks .
a couple of blocks provide tools for the analysis of ipa applications for toxicity and biomarker identification .
the comparative analysis option provides tools for analysing changes in biological states across experimental conditions .
cytoscape ,   similar to pathway studio , is an installable program that resides on your computer .
it is a collaborative effort of the institute for systems biology ( isb ; seattle , wa ) , ucsd , sloan - kettering cancer center , institut pasteur , agilent technologies and the university of california , san francisco .
cytoscape is available as a platform - independent open - source java application and can be installed in windows , mac osx or linux environments with at least 256 mb ram . by contrast with pathway studio , cytoscape has the ability to connect to external data sources , either directly or using plug - ins .
most are free , but some cost a small amount of money . from these plug - ins
, cytoscape users can connect to intact , kegg , pathway commons and several other interaction databases .
the cytoscape application programming interface ( api ) is available publicly , so with the proper training , many scientists can create plug - ins unique to their projects . to compare the functionality of cytoscape ,
pathway studio and ipa , two tests were performed , based on the expectations of what a typical scientists would do .
the two tests were : ( i ) searching for key terms associated with disease and treatment to build a network and ( ii ) importing expression data from an experiment associated with a disease state , and using that data to create a network .
two machines were used to test the three software packages : an hp pavilion tower desktop with windows vista with an intel core 2 quad processor and 8 gb systems memory to test pathway studio 7.0 , and an apple macbook running os 10.5 with an intel core 2 duo processor and 2 gb of ram to test cytoscape 2.6.3 and ipa 8.0 versions .
common usage of these packages requires the ability to search specific genes and keywords associated with a gene , protein or molecular function .
each software solution allows for searching of gene ontology indexes , but a more important function is the ability to identify genes , proteins or molecules associated with key terms . in the present analysis ,
two key terms were used : ( i ) ' resistance ' , for finding networks associated with drug resistance ; and ( ii ) ' migration ' , with the intention of identifying networks associated with metastasis .
another key function that has become available in the past two years is importing data from mrna - based expression platforms and building a network associated with a specific experiment .
the algorithms range from simple searches of the gene symbols to de novo network discovery based on expression patterns . this analysis used data from 27 patients with adenocarcinoma of the lung , with the data generated by an affymetrix human 133a chip .
the entities were of two categories : ( i ) genes / proteins and other molecules , and ( ii ) functions or groups .
the top ten proteins and top ten terms for function or group with their frequencies , as produced by pathway studio software 7.0 , using the keyword ' resistance ' . * nf , nuclear factor ; tnf , tumour necrosis factor * numbers in parentheses are the numbers of protein in each group .
the search for ' migration ' using pathway studio produced 2,293 entities and 7,218 interactions : 5,852 regulations , 1,011 expressions , as well as some protein modifications , molecular transport , promoter binding , and molecular synthesis .
the top ten proteins and top ten terms for function or group with their frequencies , as produced by pathway studio software , using the keyword ' migration ' nf , nuclear factor ; tnf , tumour necrosis factor * numbers in parentheses are the numbers of proteins in each group .
the pathway studio ' gene sets enrichment analysis ' ( gsea ) function offers additional analysis by which the user can identify commonly occurring gene ontology keywords in their network .
the available options are : ariadne metabolic pathways , ariadne signaling pathways , users pathways , ariadne ontologies , gene ontology cellular components , gene ontology molecular functions , gene ontology biological processes and users groups . in the authors ' analysis ,
the software provides a comparison of the number of entities found in the user 's network and in the entire category .
it also provides the number and names of nodes that are found in more than one category , a p value and a ranking .
the ' resistance ' search resulted in a list of 331 categories ; the top two ranked were ' atpase activity ' , with p values of 2.13 eand 2.67 e. the ' migration ' search produced a list of 234 categories ; the top two were ' inflammatory response ' and ' cytosol ' , with p values of 4.86 eand 1.11 e , respectively .
it allows the user to search for three categories of information : ' genes and chemicals ' , ' functions and diseases ' and ' pathways and tox lists ' .
after the initial search , the results can be further refined by selecting specific groups of the genes , proteins and molecules found .
in addition , however , the results in ipa are in graphical form for easy analysis , showing the results as bar graphs and the significance overlaid as a line graph . in the authors ' analysis , they selected the top two categories , ' cancer ' and ' drug resistance based keywords ' for the resistance search , and ' cell migration keywords ' for the migration search .
the ' resistance ' search produced a network of 91 nodes and 533 links associated with the search term and the two keywords .
as with pathway studio , ipa allows the user to adjust the views of the network based on cellular compartment and functional groups , as well as to view more information by selecting nodes and edges .
when the authors attempted to visualise the network for migration , they ran into the 500-node limit on visualisation within ipa 's viewer . to get around this limitation , they had to refine their search further by selecting two more keywords ( ' cancer ' and ' drug resistance ' ) .
cytoscape also allows keyword searching through ' import ' from the ' network from web services ' function .
depending upon the database , the time and size of the resulting set can be controlled .
the authors chose to search the pathway commons database for their analysis . when searching this database , it is possible to specify the species to search and to import curated pathways or all interactions associated with the search result . to do the latter
, one selects the protein i d or gene name reported as a search result , selects the tab labelled ' interaction networks ' and then selects ' retrieve interactions ' .
the authors used this process for both of their search terms . for ' resistance ' ,
one can adjust how these results are viewed by selecting a specific layout from the layout menu ( as with ipa ) or import a third - party plug - in to create layouts based on node characteristics .
in addition to layouts , one can calculate network topology statistics to identify the most connected nodes , most central nodes , most eccentric nodes and many more .
top ten terms found by cytoscape software searching the pathway commons database for key words ' migration ' and ' resistance ' .
human due to the availability of more than one database , the authors chose to search intact , as well as pathway commons , using cytoscape .
the intact search function can be accessed from the same menu and allows the search to be limited by time and size of result set .
the search for ' migration ' using pathway commons produced a network of 1,166 nodes and 13,755 links .
the same search of the intact database produced a network of 3,250 nodes , with 8,799 interactions .
thus , cytoscape produced networks containing more interactions than pathway studio- and ingenuity - based networks .
another key function that has become available with all three software packages over the past couple of years is the facility to import data from mrna - based expression platforms and building a network associated with a specific experiment .
the algorithms range from simple searches of gene symbols to de novo network discovery based on expression patterns .
pathway studio offers a function for performing a comparative analysis of imported multiple gene expression , proteomics and metabolomics experiments .
a user can select the platform for generating the data and the column with the matching probe ids .
pathway studio requires the entire dataset to be uploaded as one table , but allows the user to select normal and abnormal columns .
the results from analysis provide a heat map of the diseased and normal expression and the p value associated with the uploaded data .
the data can then be correlated and used to generate a network , or be overlaid onto a network from the resnet database or from a medscan v. 3.0 search .
the correlation analysis is limited to pairwise correlations and can not be used to infer interaction , but may provide additional insight into the data .
most commonly used formats are available , except the newer xml - based excel format .
after uploading the data , the user is prompted to select the commercial mrna platform ( human u133a or similar ) to generate the data .
ipa limits the number of experimental data columns to 20 , so some of the authors ' 27 columns could not be uploaded .
additional menus allow for modifications to the search and analysis options . modifying these options would limit the scope of the search results , with the hope of increasing the accuracy , while reducing the size of the set of results .
for the authors ' study set , ipa generated 20 unique networks that showed little overlap .
the expression data are overlaid onto each node , and each network is created based on the highest - fold change in the data .
cytoscape functions for experimental data analysis are available as third - party plug - ins . at the time of writing , there are two types of such plug - ins : expression overlay ( similar to ipa ) and network inference .
the plug - in genoscape has been developed in a collaboration between scientists at several leading european institutions .
additionally , a user can create a tab - delineated file of original gene expression data to import into genoscape .
the plug - in visualises gene expression changes for each node and provides statistical analysis of the significance of these changes .
cytoscape also allows users to import gene expression , proteomics or metabolomics data through the network attribute import function . after selecting an attribute file to import ,
cytoscape allows the user to select a column to map the expression to nodes , and to identify the columns with expression data .
after the gene expression data are imported , the vismapper tool can be used to visualise the expression by colour on the nodes .
currently , most networks are created by searching databases of curated literature - sourced interactions like resnet and intact .
network builder is a new plug - in that allows the user to infer interactions from gene expression or mass spectrometry data .
an example of how this type of network creation can be used in the search for lung cancer biomarkers is presented in kuznetsov et al .
pathway studio ( ariadne genomics , rockville , md ) is a software which builds networks and pathways from relationships between biological molecules and processes extracted from the literature , pubmed , databases , expression and proteomics data .
pathway studio is offered with the resnet mammalian and resnet plant databases , and supports kegg , science signaling and prolexys hynet protein - protein interaction databases .
the resnet 7.0 database contains over 1.5 million relationships for 110,435 proteins , 814 cellular processes , 2,410 diseases and 248 curated pathways .
the resnet plant database includes over 90,000 relationships for 71,501 proteins , 915 cellular processes , 97 plant diseases , and 315 aracyc and 17 plant signalling pathways .
the software also calculates the node degrees in the network built , and compares them with the node degrees in the resnet database .
pathway studio enterprise includes server - side applications with windows , linux and solaris , compared with the client - side windows ( xp , vista and 7 ) applications of the desktop version .
the desktop version of pathway studio 7.0 requires a minimum of 2 gb ram , while 4 gb are recommended .
the server makes use of two or more quad - core intel / amd processors with 4 - 10 gb ram and 32-/64-bit operating system ( os ) and java virtual machine ( jvm ) -- a crucial component of the java platform .
a java - based start - up application downloads to your machine and initiates the connection to ingenuity systems back - end server infrastructure .
this allows ipa to be run on any machine with a web interface running most versions of windows , from xp to 7 , and max os 10.4.2 to 10.6.2 .
the most recent ipa 8.0 version requires a minimum of 512 mb of ram but recommends 1 gb for windows xp and mac os x , and 2 gb under vista and windows 7 .
ipa uses a database for human genes / proteins , created from manually curated literature searches ( ingenuityexpertassist findings ) .
specific data on the number of interactions and the number of molecules is not reported .
ipa also includes interaction data from third party databases , such as intact , bind , dip , mint , mips , biogrid and cognia .
the core analysis is the basic block for analysis of protein - protein interaction networks .
a couple of blocks provide tools for the analysis of ipa applications for toxicity and biomarker identification .
the comparative analysis option provides tools for analysing changes in biological states across experimental conditions .
cytoscape ,   similar to pathway studio , is an installable program that resides on your computer .
it is a collaborative effort of the institute for systems biology ( isb ; seattle , wa ) , ucsd , sloan - kettering cancer center , institut pasteur , agilent technologies and the university of california , san francisco .
cytoscape is available as a platform - independent open - source java application and can be installed in windows , mac osx or linux environments with at least 256 mb ram . by contrast with pathway studio , cytoscape has the ability to connect to external data sources , either directly or using plug - ins .
most are free , but some cost a small amount of money . from these plug - ins
, cytoscape users can connect to intact , kegg , pathway commons and several other interaction databases .
the cytoscape application programming interface ( api ) is available publicly , so with the proper training , many scientists can create plug - ins unique to their projects .
to compare the functionality of cytoscape , pathway studio and ipa , two tests were performed , based on the expectations of what a typical scientists would do .
the two tests were : ( i ) searching for key terms associated with disease and treatment to build a network and ( ii ) importing expression data from an experiment associated with a disease state , and using that data to create a network .
two machines were used to test the three software packages : an hp pavilion tower desktop with windows vista with an intel core 2 quad processor and 8 gb systems memory to test pathway studio 7.0 , and an apple macbook running os 10.5 with an intel core 2 duo processor and 2 gb of ram to test cytoscape 2.6.3 and ipa 8.0 versions .
common usage of these packages requires the ability to search specific genes and keywords associated with a gene , protein or molecular function .
each software solution allows for searching of gene ontology indexes , but a more important function is the ability to identify genes , proteins or molecules associated with key terms . in the present analysis , two key terms were used : ( i ) ' resistance ' , for finding networks associated with drug resistance ; and ( ii ) ' migration ' , with the intention of identifying networks associated with metastasis .
another key function that has become available in the past two years is importing data from mrna - based expression platforms and building a network associated with a specific experiment .
the algorithms range from simple searches of the gene symbols to de novo network discovery based on expression patterns . this analysis used data from 27 patients with adenocarcinoma of the lung , with the data generated by an affymetrix human 133a chip .
the entities were of two categories : ( i ) genes / proteins and other molecules , and ( ii ) functions or groups .
the top ten proteins and top ten terms for function or group with their frequencies , as produced by pathway studio software 7.0 , using the keyword ' resistance ' . * nf , nuclear factor ; tnf , tumour necrosis factor * numbers in parentheses are the numbers of protein in each group .
the search for ' migration ' using pathway studio produced 2,293 entities and 7,218 interactions : 5,852 regulations , 1,011 expressions , as well as some protein modifications , molecular transport , promoter binding , and molecular synthesis .
the top ten proteins and top ten terms for function or group with their frequencies , as produced by pathway studio software , using the keyword ' migration ' nf , nuclear factor ; tnf , tumour necrosis factor * numbers in parentheses are the numbers of proteins in each group .
the pathway studio ' gene sets enrichment analysis ' ( gsea ) function offers additional analysis by which the user can identify commonly occurring gene ontology keywords in their network .
the available options are : ariadne metabolic pathways , ariadne signaling pathways , users pathways , ariadne ontologies , gene ontology cellular components , gene ontology molecular functions , gene ontology biological processes and users groups . in the authors ' analysis ,
the software provides a comparison of the number of entities found in the user 's network and in the entire category .
it also provides the number and names of nodes that are found in more than one category , a p value and a ranking .
the ' resistance ' search resulted in a list of 331 categories ; the top two ranked were ' atpase activity ' , with p values of 2.13 eand 2.67 e. the ' migration ' search produced a list of 234 categories ; the top two were ' inflammatory response ' and ' cytosol ' , with p values of 4.86 eand 1.11 e , respectively .
it allows the user to search for three categories of information : ' genes and chemicals ' , ' functions and diseases ' and ' pathways and tox lists ' .
after the initial search , the results can be further refined by selecting specific groups of the genes , proteins and molecules found .
in addition , however , the results in ipa are in graphical form for easy analysis , showing the results as bar graphs and the significance overlaid as a line graph . in the authors ' analysis , they selected the top two categories , ' cancer ' and ' drug resistance based keywords ' for the resistance search , and ' cell migration keywords ' for the migration search .
the ' resistance ' search produced a network of 91 nodes and 533 links associated with the search term and the two keywords .
as with pathway studio , ipa allows the user to adjust the views of the network based on cellular compartment and functional groups , as well as to view more information by selecting nodes and edges .
when the authors attempted to visualise the network for migration , they ran into the 500-node limit on visualisation within ipa 's viewer . to get around this limitation , they had to refine their search further by selecting two more keywords ( ' cancer ' and ' drug resistance ' ) .
cytoscape also allows keyword searching through ' import ' from the ' network from web services ' function .
the user needs first to select the database and then to execute the search . depending upon the database
when searching this database , it is possible to specify the species to search and to import curated pathways or all interactions associated with the search result . to do the latter , one selects the protein i d or gene name reported as a search result , selects the tab labelled ' interaction networks ' and then selects ' retrieve interactions ' .
the authors used this process for both of their search terms . for ' resistance ' ,
one can adjust how these results are viewed by selecting a specific layout from the layout menu ( as with ipa ) or import a third - party plug - in to create layouts based on node characteristics .
in addition to layouts , one can calculate network topology statistics to identify the most connected nodes , most central nodes , most eccentric nodes and many more .
top ten terms found by cytoscape software searching the pathway commons database for key words ' migration ' and ' resistance ' . *
human due to the availability of more than one database , the authors chose to search intact , as well as pathway commons , using cytoscape .
the intact search function can be accessed from the same menu and allows the search to be limited by time and size of result set .
the search for ' migration ' using pathway commons produced a network of 1,166 nodes and 13,755 links .
the same search of the intact database produced a network of 3,250 nodes , with 8,799 interactions .
thus , cytoscape produced networks containing more interactions than pathway studio- and ingenuity - based networks .
another key function that has become available with all three software packages over the past couple of years is the facility to import data from mrna - based expression platforms and building a network associated with a specific experiment .
the algorithms range from simple searches of gene symbols to de novo network discovery based on expression patterns .
pathway studio offers a function for performing a comparative analysis of imported multiple gene expression , proteomics and metabolomics experiments .
a user can select the platform for generating the data and the column with the matching probe ids .
pathway studio requires the entire dataset to be uploaded as one table , but allows the user to select normal and abnormal columns .
the results from analysis provide a heat map of the diseased and normal expression and the p value associated with the uploaded data .
the data can then be correlated and used to generate a network , or be overlaid onto a network from the resnet database or from a medscan v. 3.0 search .
the correlation analysis is limited to pairwise correlations and can not be used to infer interaction , but may provide additional insight into the data .
most commonly used formats are available , except the newer xml - based excel format .
after uploading the data , the user is prompted to select the commercial mrna platform ( human u133a or similar ) to generate the data .
ipa limits the number of experimental data columns to 20 , so some of the authors ' 27 columns could not be uploaded .
modifying these options would limit the scope of the search results , with the hope of increasing the accuracy , while reducing the size of the set of results .
for the authors ' study set , ipa generated 20 unique networks that showed little overlap .
the expression data are overlaid onto each node , and each network is created based on the highest - fold change in the data .
cytoscape functions for experimental data analysis are available as third - party plug - ins . at the time of writing , there are two types of such plug - ins : expression overlay ( similar to ipa ) and network inference . the plug - in genoscape has been developed in a collaboration between scientists at several leading european institutions .
additionally , a user can create a tab - delineated file of original gene expression data to import into genoscape .
the plug - in visualises gene expression changes for each node and provides statistical analysis of the significance of these changes .
cytoscape also allows users to import gene expression , proteomics or metabolomics data through the network attribute import function . after selecting an attribute file to import ,
cytoscape allows the user to select a column to map the expression to nodes , and to identify the columns with expression data .
after the gene expression data are imported , the vismapper tool can be used to visualise the expression by colour on the nodes .
currently , most networks are created by searching databases of curated literature - sourced interactions like resnet and intact .
network builder is a new plug - in that allows the user to infer interactions from gene expression or mass spectrometry data .
an example of how this type of network creation can be used in the search for lung cancer biomarkers is presented in kuznetsov et al .
common usage of these packages requires the ability to search specific genes and keywords associated with a gene , protein or molecular function .
each software solution allows for searching of gene ontology indexes , but a more important function is the ability to identify genes , proteins or molecules associated with key terms . in the present analysis , two key terms were used : ( i ) ' resistance ' , for finding networks associated with drug resistance ; and ( ii ) ' migration ' , with the intention of identifying networks associated with metastasis .
another key function that has become available in the past two years is importing data from mrna - based expression platforms and building a network associated with a specific experiment .
the algorithms range from simple searches of the gene symbols to de novo network discovery based on expression patterns . this analysis used data from 27 patients with adenocarcinoma of the lung , with the data generated by an affymetrix human 133a chip .
the entities were of two categories : ( i ) genes / proteins and other molecules , and ( ii ) functions or groups .
the top ten proteins and top ten terms for function or group with their frequencies , as produced by pathway studio software 7.0 , using the keyword ' resistance ' . * nf , nuclear factor ; tnf , tumour necrosis factor * numbers in parentheses are the numbers of protein in each group . cell process ; disease ; functional class .
the search for ' migration ' using pathway studio produced 2,293 entities and 7,218 interactions : 5,852 regulations , 1,011 expressions , as well as some protein modifications , molecular transport , promoter binding , and molecular synthesis .
the top ten proteins and top ten terms for function or group with their frequencies , as produced by pathway studio software , using the keyword ' migration ' nf , nuclear factor ; tnf , tumour necrosis factor * numbers in parentheses are the numbers of proteins in each group .
the pathway studio ' gene sets enrichment analysis ' ( gsea ) function offers additional analysis by which the user can identify commonly occurring gene ontology keywords in their network .
the available options are : ariadne metabolic pathways , ariadne signaling pathways , users pathways , ariadne ontologies , gene ontology cellular components , gene ontology molecular functions , gene ontology biological processes and users groups . in the authors ' analysis ,
the software provides a comparison of the number of entities found in the user 's network and in the entire category .
it also provides the number and names of nodes that are found in more than one category , a p value and a ranking .
the ' resistance ' search resulted in a list of 331 categories ; the top two ranked were ' atpase activity ' , with p values of 2.13 eand 2.67 e. the ' migration ' search produced a list of 234 categories ; the top two were ' inflammatory response ' and ' cytosol ' , with p values of 4.86 eand 1.11 e , respectively .
it allows the user to search for three categories of information : ' genes and chemicals ' , ' functions and diseases ' and ' pathways and tox lists ' .
after the initial search , the results can be further refined by selecting specific groups of the genes , proteins and molecules found .
in addition , however , the results in ipa are in graphical form for easy analysis , showing the results as bar graphs and the significance overlaid as a line graph . in the authors ' analysis , they selected the top two categories , ' cancer ' and ' drug resistance based keywords ' for the resistance search , and ' cell migration keywords ' for the migration search .
the ' resistance ' search produced a network of 91 nodes and 533 links associated with the search term and the two keywords .
as with pathway studio , ipa allows the user to adjust the views of the network based on cellular compartment and functional groups , as well as to view more information by selecting nodes and edges .
when the authors attempted to visualise the network for migration , they ran into the 500-node limit on visualisation within ipa 's viewer . to get around this limitation , they had to refine their search further by selecting two more keywords ( ' cancer ' and ' drug resistance ' ) .
cytoscape also allows keyword searching through ' import ' from the ' network from web services ' function .
the user needs first to select the database and then to execute the search . depending upon the database , the time and size of the resulting set
when searching this database , it is possible to specify the species to search and to import curated pathways or all interactions associated with the search result . to do the latter
, one selects the protein i d or gene name reported as a search result , selects the tab labelled ' interaction networks ' and then selects ' retrieve interactions ' . the protein or gene names associated with each search are reported in table 3 .
the authors used this process for both of their search terms . for ' resistance ' ,
one can adjust how these results are viewed by selecting a specific layout from the layout menu ( as with ipa ) or import a third - party plug - in to create layouts based on node characteristics .
in addition to layouts , one can calculate network topology statistics to identify the most connected nodes , most central nodes , most eccentric nodes and many more .
top ten terms found by cytoscape software searching the pathway commons database for key words ' migration ' and ' resistance ' .
human due to the availability of more than one database , the authors chose to search intact , as well as pathway commons , using cytoscape .
the intact search function can be accessed from the same menu and allows the search to be limited by time and size of result set .
the search for ' migration ' using pathway commons produced a network of 1,166 nodes and 13,755 links .
the same search of the intact database produced a network of 3,250 nodes , with 8,799 interactions .
thus , cytoscape produced networks containing more interactions than pathway studio- and ingenuity - based networks .
another key function that has become available with all three software packages over the past couple of years is the facility to import data from mrna - based expression platforms and building a network associated with a specific experiment .
the algorithms range from simple searches of gene symbols to de novo network discovery based on expression patterns .
pathway studio offers a function for performing a comparative analysis of imported multiple gene expression , proteomics and metabolomics experiments .
a user can select the platform for generating the data and the column with the matching probe ids .
pathway studio requires the entire dataset to be uploaded as one table , but allows the user to select normal and abnormal columns .
the results from analysis provide a heat map of the diseased and normal expression and the p value associated with the uploaded data .
the data can then be correlated and used to generate a network , or be overlaid onto a network from the resnet database or from a medscan v. 3.0 search .
the correlation analysis is limited to pairwise correlations and can not be used to infer interaction , but may provide additional insight into the data .
most commonly used formats are available , except the newer xml - based excel format .
after uploading the data , the user is prompted to select the commercial mrna platform ( human u133a or similar ) to generate the data .
ipa limits the number of experimental data columns to 20 , so some of the authors ' 27 columns could not be uploaded .
additional menus allow for modifications to the search and analysis options . modifying these options would limit the scope of the search results , with the hope of increasing the accuracy , while reducing the size of the set of results .
for the authors ' study set , ipa generated 20 unique networks that showed little overlap .
the expression data are overlaid onto each node , and each network is created based on the highest - fold change in the data .
cytoscape functions for experimental data analysis are available as third - party plug - ins . at the time of writing , there are two types of such plug - ins : expression overlay ( similar to ipa ) and network inference . the plug - in genoscape has been developed in a collaboration between scientists at several leading european institutions .
additionally , a user can create a tab - delineated file of original gene expression data to import into genoscape .
the plug - in visualises gene expression changes for each node and provides statistical analysis of the significance of these changes .
cytoscape also allows users to import gene expression , proteomics or metabolomics data through the network attribute import function . after selecting an attribute file to import
, cytoscape allows the user to select a column to map the expression to nodes , and to identify the columns with expression data .
after the gene expression data are imported , the vismapper tool can be used to visualise the expression by colour on the nodes .
currently , most networks are created by searching databases of curated literature - sourced interactions like resnet and intact .
network builder is a new plug - in that allows the user to infer interactions from gene expression or mass spectrometry data .
an example of how this type of network creation can be used in the search for lung cancer biomarkers is presented in kuznetsov et al .
the three basic software packages for network analysis discussed here offer similar functions and tools .
the commercial pathway studio and ipa packages produce more visually appealing networks , but limit the number of analytical tools available to the user .
cytoscape , as an open - source software package , has been developed by a community of scientists and programmers from different universities and research institutions , collaborating to create better tools .
ipa and pathway studio offer less of a development community , but provide a more refined and stable software solution .
it is difficult to predict where the future of these software tools lies , but one may expect them to become even more universal by including blocks or plug - ins for substructure analysis ( modules and motifs ) and calculation of network descriptors ( such as based on connectivity , distances , centrality , clustering , etc . ) .
being a more flexible dynamic structure , the cytoscape community shows promise as a future front - runner for this type of scientific software ; however , ipa and pathway studio will continue to be strong and very popular , with their online training videos , webinars and specialised conferences devoted to the software applications .
reasonable advice to researchers interested in network analysis applications is to use at least two of the leading software packages and rely on the results that overlap .
currently , proprietary databases are the key sources of network generation . with the advancement of the national institutes of health- and european bioinformatics institute - supported interaction databases , and their rapid weekly update schedule
pathway studio 's medscan function is an obvious response to this challenge , and offers an excellent way of producing the most up - to - date version of an interaction database .
this database is generated by a text - based search of recent publications , as with medscan , but these are reviewed manually to verify the validity of the interactions .
systems biology continues to grow and is quickly moving from academic laboratories to commercial r&d .
network discovery and analysis will become increasingly more important in the study of gene signalling and molecular communication in biology and biomedical research , as well as in the field of drug design .
this growth will provide more resources to expand the currently existing software solutions , and will , without doubt , bring better network - based technology and more powerful analytical tools in the very near future .
 software for network motifs and modules is briefly reviewed , along with programs for network comparison . 
 the three major software packages for network analysis , cytoscape , ingenuity and pathway studio , and their associated databases , are compared in detail . 
 a comparative test evaluated how these software packages perform the search for key terms and the creation of network from those terms and from experimental expression data . 
Introduction to network-related software tools
Basic software for network analysis: Pathway Studio, Ingenuity Pathway Analysis (IPA) and Cytoscape
Technical specifications
Analysis
Method of analysis
Analysis of results: Searches
Analysis of results: Building and analysing a network from experimental data
Conclusion