http://wiki.c2b2.columbia.edu/workbench/api.php?action=feedcontributions&feedformat=atom&user=MhoniggeWorkbench - User contributions [en]2026-04-30T04:24:52ZUser contributionsMediaWiki 1.27.7http://wiki.c2b2.columbia.edu/workbench/index.php?title=Home&diff=12504Home2015-01-06T18:04:36Z<p>Mhonig: </p>
<hr />
<div>__NOTOC__<br />
<sgallery width="700" showinfopane="false" timed="true" delay="4000" showcarousel="false"><br />
ARACNe_with_t-test_home_gallery.PNG<br />
MarkUs_home_gallery.PNG<br />
Dendrogram_home_gallery.PNG<br />
Volcano_plot_home_gallery.PNG<br />
JMol_viewer_home_gallery.PNG<br />
Skybase_home_gallery.PNG<br />
TF_binding_site_prediction_home_gallery.PNG<br />
Motif_discovery_home_gallery.PNG<br />
BLAST_home_gallery.PNG<br />
CCM_home_gallery.PNG<br />
Gene_Ontology_home_gallery.PNG<br />
</sgallery><br />
<br />
{| class="wikitable" style="background-color:#F8EDD6;" cellpadding="10" width="700px"<br />
|colspan="2"|<br />
<h2>Overview</h2><br />
'''geWorkbench''' (<u>ge</u>nomics <u>Workbench</u>) is a Java-based open-source platform for integrated genomics. Using a component architecture it allows individually developed plug-ins to be configured into complex bioinformatic applications. At present there are more than 70 available [[Plugins|plug-ins]] supporting the visualization and analysis of gene expression and sequence data. Example use cases include: <toggledisplay status="hide"><br />
* loading data from local or remote data sources.<br />
* visualizing gene expression, molecular interaction networks, protein sequence and protein structure data in a variety of ways.<br />
* providing access to client- and server-side computational analysis tools such as t-test analysis, hierarchical clustering, self organizing maps, regulatory neworks reconstruction, BLAST searches, pattern/motif discovery, etc.<br />
* validating computational hypothesis through the integration of gene and pathway annotation information from curated sources as well as through Gene Ontology enrichment analysis.<br />
<br/><br />
geWorkbench is the Bioinformatics platform of [http://magnet.c2b2.columbia.edu MAGNet], the '''National Center for the Multi-scale Analysis of Genomic and Cellular Networks''' (one of the [http://www.ncbcs.org 7 National Centers for Biomedial Computing] funded through the [http://nihroadmap.nih.gov/ NIH Common Fund]). <br />
<!-- <br />
In the past, geWorkbench has received support from [https://cabig.nci.nih.gov/ caBIG<sup>&reg;</sup>, NCI's cancer Biomedical Informatics Grid initiative].<br />
<br />
<br/><br />
End-user and developer support for geWorkbench is provided through the caBIG<sup>&reg;</sup> [https://cabig-kc.nci.nih.gov/Molecular/KC/index.php/Main_Page Molecular Analysis Tools Knowledge Center], a component of the caBIG<sup>&reg;</sup> [https://cabig.nci.nih.gov/esn/ Enterprise Support Network].<br />
--><br />
</toggledisplay><br />
|-<br />
| style="width: 50%; background-color: #F2F8C7;"|<br />
<h2>Quick Start</h2><br />
Please see the [[QuickStart| Quick Start]] guide to geWorkbench to see how to get started using geWorkbench right away. <br />
| style="width: 50%; background-color: #C7F8CB;"|<br />
<h2>Current Release</h2><br />
The latest production version of geWorkbench (v2.5.1) was released on November 1st, 2013.<br />
* [[Release_Descriptions#Brief_overview_of_changes_in_geWorkbench_release_2.5.1|See changes included in latest release]].<br />
* [[Release_Descriptions|See history of past releases]].<br />
* [[Download_and_Installation|Download geWorkbench]].<br />
|-<br />
|style="background-color: #D8FAFA;" colspan="2"|<br />
''<h4><center><font color="red">New web-enabled version available</font></center></h4>''<br />
'''geWorkbench-Web''' provides installation-free access to the geWorkbench plug-ins through a pure browser interface. A beta release is available for testing at: http://geworkbench.c2b2.columbia.edu/geworkbench/. <br />
|}</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Home&diff=12503Home2015-01-06T18:04:06Z<p>Mhonig: </p>
<hr />
<div>__NOTOC__<br />
<sgallery width="700" showinfopane="false" timed="true" delay="4000" showcarousel="false"><br />
ARACNe_with_t-test_home_gallery.PNG<br />
MarkUs_home_gallery.PNG<br />
Dendrogram_home_gallery.PNG<br />
Volcano_plot_home_gallery.PNG<br />
JMol_viewer_home_gallery.PNG<br />
Skybase_home_gallery.PNG<br />
TF_binding_site_prediction_home_gallery.PNG<br />
Motif_discovery_home_gallery.PNG<br />
BLAST_home_gallery.PNG<br />
CCM_home_gallery.PNG<br />
Gene_Ontology_home_gallery.PNG<br />
</sgallery><br />
<br />
{| class="wikitable" style="background-color:#F8EDD6;" cellpadding="10" width="700px"<br />
|colspan="2"|<br />
<h2>Overview</h2><br />
'''geWorkbench1''' (<u>ge</u>nomics <u>Workbench</u>) is a Java-based open-source platform for integrated genomics. Using a component architecture it allows individually developed plug-ins to be configured into complex bioinformatic applications. At present there are more than 70 available [[Plugins|plug-ins]] supporting the visualization and analysis of gene expression and sequence data. Example use cases include: <toggledisplay status="hide"><br />
* loading data from local or remote data sources.<br />
* visualizing gene expression, molecular interaction networks, protein sequence and protein structure data in a variety of ways.<br />
* providing access to client- and server-side computational analysis tools such as t-test analysis, hierarchical clustering, self organizing maps, regulatory neworks reconstruction, BLAST searches, pattern/motif discovery, etc.<br />
* validating computational hypothesis through the integration of gene and pathway annotation information from curated sources as well as through Gene Ontology enrichment analysis.<br />
<br/><br />
geWorkbench is the Bioinformatics platform of [http://magnet.c2b2.columbia.edu MAGNet], the '''National Center for the Multi-scale Analysis of Genomic and Cellular Networks''' (one of the [http://www.ncbcs.org 7 National Centers for Biomedial Computing] funded through the [http://nihroadmap.nih.gov/ NIH Common Fund]). <br />
<!-- <br />
In the past, geWorkbench has received support from [https://cabig.nci.nih.gov/ caBIG<sup>&reg;</sup>, NCI's cancer Biomedical Informatics Grid initiative].<br />
<br />
<br/><br />
End-user and developer support for geWorkbench is provided through the caBIG<sup>&reg;</sup> [https://cabig-kc.nci.nih.gov/Molecular/KC/index.php/Main_Page Molecular Analysis Tools Knowledge Center], a component of the caBIG<sup>&reg;</sup> [https://cabig.nci.nih.gov/esn/ Enterprise Support Network].<br />
--><br />
</toggledisplay><br />
|-<br />
| style="width: 50%; background-color: #F2F8C7;"|<br />
<h2>Quick Start</h2><br />
Please see the [[QuickStart| Quick Start]] guide to geWorkbench to see how to get started using geWorkbench right away. <br />
| style="width: 50%; background-color: #C7F8CB;"|<br />
<h2>Current Release</h2><br />
The latest production version of geWorkbench (v2.5.1) was released on November 1st, 2013.<br />
* [[Release_Descriptions#Brief_overview_of_changes_in_geWorkbench_release_2.5.1|See changes included in latest release]].<br />
* [[Release_Descriptions|See history of past releases]].<br />
* [[Download_and_Installation|Download geWorkbench]].<br />
|-<br />
|style="background-color: #D8FAFA;" colspan="2"|<br />
''<h4><center><font color="red">New web-enabled version available</font></center></h4>''<br />
'''geWorkbench-Web''' provides installation-free access to the geWorkbench plug-ins through a pure browser interface. A beta release is available for testing at: http://geworkbench.c2b2.columbia.edu/geworkbench/. <br />
|}</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Overview&diff=10652Overview2013-02-12T00:08:03Z<p>Mhonig: </p>
<hr />
<div>__NOEDITSECTION__<br />
==Introduction==<br />
<br />
geWorkbench is an open-source bioinformatics platform that offers a comprehensive and extensible collection of tools for the management, analysis, visualization and annotation of biomedical data. Many kinds of analysis are supported - for microarrays, there are filtering and normalization, basic statistical analyses, clustering, network reverse engineering, as well as many common visualization tools. For sequence data there are routines such as BLAST, pattern detection, transcription factor mapping, and syntenic region analysis. Furthermore, genomic sequences around markers of interest found in microarray experiments can be easily retrieved and, for example, used for promoter/transcription factor analysis.<br />
<br />
Specific types of data supported include:<br />
<br />
*Microarray Gene Expression<br />
** GEO Soft: Series, Series Matrix, and Annotated Matrix (GDS)<br />
** MAGE-TAB data matrix<br />
**Affymetrix GCOS/MAS5<br />
**Matrix format (geWorkbench)<br />
**Tab-delimited (e.g. RMAExpress)<br />
**GenePix<br />
* Microarray Gene Expression Annotation file support<br />
** Affymetrix 3' Expression<br />
** Affymetrix WT Gene/Exon ST (transcript-level) including Gene Array 1.0/2.0 ST and Exon 1.0 ST.<br />
*DNA and Protein Sequences<br />
**FASTA<br />
*Pathways<br />
**BioCarta<br />
*Molecular structure - prediction, annotation and display<br />
*Sequence Patterns<br />
**Regular Expressions<br />
*Gene Ontology<br />
*Regulatory Networks<br />
<br />
Most importantly, geWorkbench provides an environment which supports moving from one data type to another in a seamless fashion, e.g. from gene expression to sequences to patterns.<br />
<br />
[[Image:slide1.gif]]<br />
<br />
<br />
==geWorkbench as an interface to external data and computational resources==<br />
<br />
geWorkbench provides access to a variety of external data sources, including:<br />
*Microarray gene expression repositories (caArray)<br />
*BLAST<br />
*Gene annotation pages (via caBIO)<br />
*Protein and DNA sequence retrieval<br />
*Pathway diagrams (BioCarta)<br />
<br />
geWorkbench also provides a gateway to several computational services currently hosted on Columbia servers and clusters, including:<br />
*Pattern Discovery<br />
*Pudge - protein structure modeling<br />
*SkyBase - database of molecular models<br />
<br />
<br />
==Basic Layout of the Graphical User Interface==<br />
<br />
<br />
The graphical user interface for geWorkbench is divided into three major sections, for<br />
<br />
# Projects - Data management (upper left)<br />
# Visualization tools (upper right)<br />
# Marker and Array/Phenotype set selection and management (lower left)<br />
<br />
<br />
[[Image:GeWorkbench_2.3.0_Main_GUI_MicroarrayViewer.png]]<br />
<br />
<br />
The Data Management area can hold one workspace, and a workspace in turn can hold one or more projects. Projects can be used as wished to group different data sets. Each opened data file or analysis result is stored in a project. A workspace and all the data it contains can be saved and returned to later.<br />
<br />
The GUI provides a menu bar at top with a standard choice of commands. Many commands that are available in the menu bar are also available by right-clicking on data objects.<br />
<br />
<br />
==Developing for geWorkbench==<br />
<br />
geWorkbench has been designed using a plug-in framework which allows new modules to be developed with relative ease. A repository will be maintained for community-developed modules. Developers can take advantage of all the existing capabilities for data management and visualization, and thus concentrate development efforts on the more important, novel aspects of their project.</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Overview&diff=10651Overview2013-02-12T00:07:52Z<p>Mhonig: </p>
<hr />
<div>__NOEDITSECTION__<br />
==Introduction==<br />
<br />
geWorkbench is an open-source bioinformatics platform that offers a comprehensive and extensible collection of tools for the management, analysis, visualization and annotation of biomedical data. Many kinds of analysis are supported - for microarrays, there are filtering and normalization, basic statistical analyses, clustering, network reverse engineering, as well as many common visualization tools. For sequence data there are routines such as BLAST, pattern detection, transcription factor mapping, and syntenic region analysis. Furthermore, genomic sequences around markers of interest found in microarray experiments can be easily retrieved and, for example, used for promoter/transcription factor analysis.<br />
<br />
Specific types of data supported include: Bloody Mary is the girl for me!<br />
<br />
*Microarray Gene Expression<br />
** GEO Soft: Series, Series Matrix, and Annotated Matrix (GDS)<br />
** MAGE-TAB data matrix<br />
**Affymetrix GCOS/MAS5<br />
**Matrix format (geWorkbench)<br />
**Tab-delimited (e.g. RMAExpress)<br />
**GenePix<br />
* Microarray Gene Expression Annotation file support<br />
** Affymetrix 3' Expression<br />
** Affymetrix WT Gene/Exon ST (transcript-level) including Gene Array 1.0/2.0 ST and Exon 1.0 ST.<br />
*DNA and Protein Sequences<br />
**FASTA<br />
*Pathways<br />
**BioCarta<br />
*Molecular structure - prediction, annotation and display<br />
*Sequence Patterns<br />
**Regular Expressions<br />
*Gene Ontology<br />
*Regulatory Networks<br />
<br />
Most importantly, geWorkbench provides an environment which supports moving from one data type to another in a seamless fashion, e.g. from gene expression to sequences to patterns.<br />
<br />
[[Image:slide1.gif]]<br />
<br />
<br />
==geWorkbench as an interface to external data and computational resources==<br />
<br />
geWorkbench provides access to a variety of external data sources, including:<br />
*Microarray gene expression repositories (caArray)<br />
*BLAST<br />
*Gene annotation pages (via caBIO)<br />
*Protein and DNA sequence retrieval<br />
*Pathway diagrams (BioCarta)<br />
<br />
geWorkbench also provides a gateway to several computational services currently hosted on Columbia servers and clusters, including:<br />
*Pattern Discovery<br />
*Pudge - protein structure modeling<br />
*SkyBase - database of molecular models<br />
<br />
<br />
==Basic Layout of the Graphical User Interface==<br />
<br />
<br />
The graphical user interface for geWorkbench is divided into three major sections, for<br />
<br />
# Projects - Data management (upper left)<br />
# Visualization tools (upper right)<br />
# Marker and Array/Phenotype set selection and management (lower left)<br />
<br />
<br />
[[Image:GeWorkbench_2.3.0_Main_GUI_MicroarrayViewer.png]]<br />
<br />
<br />
The Data Management area can hold one workspace, and a workspace in turn can hold one or more projects. Projects can be used as wished to group different data sets. Each opened data file or analysis result is stored in a project. A workspace and all the data it contains can be saved and returned to later.<br />
<br />
The GUI provides a menu bar at top with a standard choice of commands. Many commands that are available in the menu bar are also available by right-clicking on data objects.<br />
<br />
<br />
==Developing for geWorkbench==<br />
<br />
geWorkbench has been designed using a plug-in framework which allows new modules to be developed with relative ease. A repository will be maintained for community-developed modules. Developers can take advantage of all the existing capabilities for data management and visualization, and thus concentrate development efforts on the more important, novel aspects of their project.</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=CNKB_Data&diff=6623CNKB Data2010-06-18T22:09:02Z<p>Mhonig: </p>
<hr />
<div>The Cellular Networks Knowledge Base (CNKB) component in geWorkbench 2.0.0 lists the following interactomes for query. However, some data has not yet be released and is password protected, and other data sets are not yet ready for query.<br />
<br />
Data that is currently available for query is shown in light green.<br />
<br />
==CNKB Data Summary==<br />
<br />
{| border="1" cellpadding="5" cellspacing="0" style="margin:10px;"<br />
|-style="color:black;background-color:#AAFFAA;"<br />
!Name<br />
!Version<br />
!Interaction Types<br />
!Availability<br />
!Date of release<br />
!Number of interactions<br />
!Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|BCi<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|01/2008<br />
|41,727<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://thebiogrid.org/ BioGRID] <br />
|2.0.61<br />
|"protein-protein"<br />
|open<br />
|date<br />
|178,546<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://dip.doe-mbi.ucla.edu DIP]<br />
|2.4<br />
|"physical interaction","direct interaction","physical association","covalent binding","association","deacetylation reaction","acetylation reaction","phosphorylation reaction","dephosphorylation reaction"<br />
|not ready<br />
|date<br />
|39,412<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|Geneways<br />
|6.0<br />
|"protein-protein"<br />
|open<br />
|date<br />
|26,931<br />
|Rzhetsky lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_Phillips<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|12/15/2009<br />
|118,114<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_Sun<br />
|1.0<br />
|"protein-dna"<br />
|pending publication<br />
|12/15/2009<br />
|54,595<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_TCGA<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|12/15/2009<br />
|46,227<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_TCGA<br />
|2.0<br />
|"TF-modulator"<br />
|pending publication<br />
|03/15/2010<br />
|15,071<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.hprd.org/ HPRD]<br />
|8.0<br />
|"protein-protein"<br />
|open<br />
|date<br />
|44,428<br />
|Data source<br />
<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://www.ebi.ac.uk/intact IntAct]<br />
|2.0.0<br />
|"protein-protein"<br />
|not ready<br />
|date<br />
|202,052<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.reactome.org/ Reactome]<br />
|31<br />
|"neighboring_reaction","reaction","direct_complex","indirect_complex"<br />
|open<br />
|date<br />
|172,295<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://mint.bio.uniroma2.it MINT]<br />
|2.6<br />
|"physical association","colocalization","phosphorylation reaction","direct interaction","sumoylation reaction","dephosphorylation reaction","association","methylation reaction","ubiquitination reaction","covalent binding","deacetylation reaction","physical interaction","cleavage reaction","enzymatic reaction","disulfide bond","glycosylation reaction","acetylation reaction","neddylation reaction","hydroxylation reaction","deneddylation reaction"<br />
|not ready<br />
|date<br />
|18,634<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|}<br />
<br />
==Local abbreviations used==<br />
<br />
* '''BCi''' - B-Cell interactome, produced by an ARACNe run on B-Cell microarray data from the lab of Dr. Ricardo Dalla-Favera.<br />
* '''HGi''' - Human High-Grade Glioma interactome, produced by analysis of microarray data from several sources:<br />
** '''Phillips''' - data published by Phillips et al. ...<br />
** '''Sun''' - data published by Sun et al. ...<br />
** '''TCGA''' - data obtained from The Cancer Genome Atlas project (NCI).<br />
<br />
<br />
==Notes==<br />
<br />
* '''HGi version 1.0''' - interactome derived from ARACNe runs (transcriptional).<br />
* '''HGi version 2.0''' - interactome derived from a MINDy run (TCGA data only) (post-translational).</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=CNKB_Data&diff=6622CNKB Data2010-06-18T22:04:12Z<p>Mhonig: </p>
<hr />
<div>The Cellular Networks Knowledge Base (CNKB) component in geWorkbench 2.0.0 lists the following interactomes for query. However, some data has not yet be released and is password protected, and other data sets are not yet ready for query.<br />
<br />
Data that is currently available for query is shown in light green.<br />
<br />
==CNKB Data Summary==<br />
<br />
{| border="1" cellpadding="5" cellspacing="0" style="margin:10px;"<br />
|-style="color:black;background-color:#AAFFAA;"<br />
!Name<br />
!Version<br />
!Interaction Types<br />
!Availability<br />
!Date of release<br />
!Number of interactions<br />
!Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|BCi<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|01/2008<br />
|41,727<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://thebiogrid.org/ BioGRID] <br />
|2.0.61<br />
|"protein-protein"<br />
|open<br />
|date<br />
|178,546<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://dip.doe-mbi.ucla.edu DIP]<br />
|2.4<br />
|"physical interaction","direct interaction","physical association","covalent binding","association","deacetylation reaction","acetylation reaction","phosphorylation reaction","dephosphorylation reaction"<br />
|not ready<br />
|date<br />
|39,412<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|Geneways<br />
|6.0<br />
|"protein-protein"<br />
|open<br />
|date<br />
|26,931<br />
|Rzhetsky lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_Phillips<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|12/15/2009<br />
|118,114<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_Sun<br />
|1.0<br />
|"protein-dna"<br />
|pending publication<br />
|12/15/2009<br />
|54,595<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_TCGA<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|12/15/2009<br />
|46,227<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_TCGA<br />
|2.0<br />
|"TF-modulator"<br />
|pending publication<br />
|03/15/2010<br />
|15,071<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.hprd.org/ HPRD]<br />
|8.0<br />
|"protein-protein"<br />
|open<br />
|date<br />
|44,428<br />
|Data source<br />
<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://www.ebi.ac.uk/intact IntAct]<br />
|2.0.0<br />
|Interaction Types<br />
|not ready<br />
|date<br />
|number<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.reactome.org/ Reactome]<br />
|31<br />
|"neighboring_reaction","reaction","direct_complex","indirect_complex"<br />
|open<br />
|date<br />
|172,295<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://mint.bio.uniroma2.it MINT]<br />
|2.6<br />
|"physical association","colocalization","phosphorylation reaction","direct interaction","sumoylation reaction","dephosphorylation reaction","association","methylation reaction","ubiquitination reaction","covalent binding","deacetylation reaction","physical interaction","cleavage reaction","enzymatic reaction","disulfide bond","glycosylation reaction","acetylation reaction","neddylation reaction","hydroxylation reaction","deneddylation reaction"<br />
|not ready<br />
|date<br />
|18,634<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|}<br />
<br />
==Local abbreviations used==<br />
<br />
* '''BCi''' - B-Cell interactome, produced by an ARACNe run on B-Cell microarray data from the lab of Dr. Ricardo Dalla-Favera.<br />
* '''HGi''' - Human High-Grade Glioma interactome, produced by analysis of microarray data from several sources:<br />
** '''Phillips''' - data published by Phillips et al. ...<br />
** '''Sun''' - data published by Sun et al. ...<br />
** '''TCGA''' - data obtained from The Cancer Genome Atlas project (NCI).<br />
<br />
<br />
==Notes==<br />
<br />
* '''HGi version 1.0''' - interactome derived from ARACNe runs (transcriptional).<br />
* '''HGi version 2.0''' - interactome derived from a MINDy run (TCGA data only) (post-translational).</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=CNKB_Data&diff=6621CNKB Data2010-06-18T21:59:49Z<p>Mhonig: </p>
<hr />
<div>The Cellular Networks Knowledge Base (CNKB) component in geWorkbench 2.0.0 lists the following interactomes for query. However, some data has not yet be released and is password protected, and other data sets are not yet ready for query.<br />
<br />
Data that is currently available for query is shown in light green.<br />
<br />
==CNKB Data Summary==<br />
<br />
{| border="1" cellpadding="5" cellspacing="0" style="margin:10px;"<br />
|-style="color:black;background-color:#AAFFAA;"<br />
!Name<br />
!Version<br />
!Interaction Types<br />
!Availability<br />
!Date of release<br />
!Number of interactions<br />
!Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|BCi<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|date<br />
|41,727<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://thebiogrid.org/ BioGRID] <br />
|2.0.61<br />
|"protein-protein"<br />
|open<br />
|date<br />
|178,546<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://dip.doe-mbi.ucla.edu DIP]<br />
|2.4<br />
|"physical interaction","direct interaction","physical association","covalent binding","association","deacetylation reaction","acetylation reaction","phosphorylation reaction","dephosphorylation reaction"<br />
|not ready<br />
|date<br />
|39,412<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|Geneways<br />
|6.0<br />
|"protein-protein"<br />
|open<br />
|date<br />
|26,931<br />
|Rzhetsky lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_Phillips<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|date<br />
|118,114<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_Sun<br />
|1.0<br />
|"protein-dna"<br />
|pending publication<br />
|date<br />
|54,595<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_TCGA<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|date<br />
|46,227<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_TCGA<br />
|2.0<br />
|"TF-modulator"<br />
|pending publication<br />
|date<br />
|15,071<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.hprd.org/ HPRD]<br />
|8.0<br />
|"protein-protein"<br />
|open<br />
|date<br />
|44,428<br />
|Data source<br />
<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://www.ebi.ac.uk/intact IntAct]<br />
|2.0.0<br />
|Interaction Types<br />
|not ready<br />
|date<br />
|number<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.reactome.org/ Reactome]<br />
|31<br />
|"neighboring_reaction","reaction","direct_complex","indirect_complex"<br />
|open<br />
|date<br />
|172,295<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://mint.bio.uniroma2.it MINT]<br />
|2.6<br />
|"physical association","colocalization","phosphorylation reaction","direct interaction","sumoylation reaction","dephosphorylation reaction","association","methylation reaction","ubiquitination reaction","covalent binding","deacetylation reaction","physical interaction"<br />
|not ready<br />
|date<br />
|18,634<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|}<br />
<br />
==Local abbreviations used==<br />
<br />
* '''BCi''' - B-Cell interactome, produced by an ARACNe run on B-Cell microarray data from the lab of Dr. Ricardo Dalla-Favera.<br />
* '''HGi''' - Human High-Grade Glioma interactome, produced by analysis of microarray data from several sources:<br />
** '''Phillips''' - data published by Phillips et al. ...<br />
** '''Sun''' - data published by Sun et al. ...<br />
** '''TCGA''' - data obtained from The Cancer Genome Atlas project (NCI).<br />
<br />
<br />
==Notes==<br />
<br />
* '''HGi version 1.0''' - interactome derived from ARACNe runs (transcriptional).<br />
* '''HGi version 2.0''' - interactome derived from a MINDy run (TCGA data only) (post-translational).</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=CNKB_Data&diff=6620CNKB Data2010-06-18T21:53:46Z<p>Mhonig: </p>
<hr />
<div>The Cellular Networks Knowledge Base (CNKB) component in geWorkbench 2.0.0 lists the following interactomes for query. However, some data has not yet be released and is password protected, and other data sets are not yet ready for query.<br />
<br />
Data that is currently available for query is shown in light green.<br />
<br />
==CNKB Data Summary==<br />
<br />
{| border="1" cellpadding="5" cellspacing="0" style="margin:10px;"<br />
|-style="color:black;background-color:#AAFFAA;"<br />
!Name<br />
!Version<br />
!Interaction Types<br />
!Availability<br />
!Date of release<br />
!Number of interactions<br />
!Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|BCi<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|date<br />
|41,727<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://thebiogrid.org/ BioGRID] <br />
|2.0.61<br />
|"protein-protein"<br />
|open<br />
|date<br />
|178,546<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://dip.doe-mbi.ucla.edu DIP]<br />
|2.4<br />
|"physical interaction","direct interaction","physical association","covalent binding","association","deacetylation reaction","acetylation reaction","phosphorylation reaction","dephosphorylation reaction"<br />
|not ready<br />
|date<br />
|39,412<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|Geneways<br />
|6.0<br />
|"protein-protein"<br />
|open<br />
|date<br />
|26,931<br />
|Rzhetsky lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_Phillips<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|date<br />
|118,114<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_Sun<br />
|1.0<br />
|"protein-dna"<br />
|pending publication<br />
|date<br />
|54,595<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_TCGA<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|date<br />
|number<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_TCGA<br />
|2.0<br />
|protein-protein (post-translational)<br />
|pending publication<br />
|date<br />
|number<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.hprd.org/ HPRD]<br />
|8.0<br />
|"protein-protein"<br />
|open<br />
|date<br />
|44,428<br />
|Data source<br />
<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://www.ebi.ac.uk/intact IntAct]<br />
|2.0.0<br />
|Interaction Types<br />
|not ready<br />
|date<br />
|number<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.reactome.org/ Reactome]<br />
|31<br />
|"neighboring_reaction","reaction","direct_complex","indirect_complex"<br />
|open<br />
|date<br />
|172,295<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://mint.bio.uniroma2.it MINT]<br />
|2.6<br />
|protein-protein<br />
|not ready<br />
|date<br />
|18,634<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|}<br />
<br />
==Local abbreviations used==<br />
<br />
* '''BCi''' - B-Cell interactome, produced by an ARACNe run on B-Cell microarray data from the lab of Dr. Ricardo Dalla-Favera.<br />
* '''HGi''' - Human High-Grade Glioma interactome, produced by analysis of microarray data from several sources:<br />
** '''Phillips''' - data published by Phillips et al. ...<br />
** '''Sun''' - data published by Sun et al. ...<br />
** '''TCGA''' - data obtained from The Cancer Genome Atlas project (NCI).<br />
<br />
<br />
==Notes==<br />
<br />
* '''HGi version 1.0''' - interactome derived from ARACNe runs (transcriptional).<br />
* '''HGi version 2.0''' - interactome derived from a MINDy run (TCGA data only) (post-translational).</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=CNKB_Data&diff=6619CNKB Data2010-06-18T21:48:10Z<p>Mhonig: </p>
<hr />
<div>The Cellular Networks Knowledge Base (CNKB) component in geWorkbench 2.0.0 lists the following interactomes for query. However, some data has not yet be released and is password protected, and other data sets are not yet ready for query.<br />
<br />
Data that is currently available for query is shown in light green.<br />
<br />
==CNKB Data Summary==<br />
<br />
{| border="1" cellpadding="5" cellspacing="0" style="margin:10px;"<br />
|-style="color:black;background-color:#AAFFAA;"<br />
!Name<br />
!Version<br />
!Interaction Types<br />
!Availability<br />
!Date of release<br />
!Number of interactions<br />
!Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|BCi<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|date<br />
|41,727<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://thebiogrid.org/ BioGRID] <br />
|2.0.61<br />
|"protein-protein"<br />
|open<br />
|date<br />
|178,546<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://dip.doe-mbi.ucla.edu DIP]<br />
|2.4<br />
|"physical interaction","direct interaction","physical association","covalent binding","association","deacetylation reaction","acetylation reaction","phosphorylation reaction","dephosphorylation reaction"<br />
|not ready<br />
|date<br />
|39,412<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|Geneways<br />
|6.0<br />
|"protein-protein"<br />
|open<br />
|date<br />
|26,931<br />
|Rzhetsky lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_Phillips<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|date<br />
|118,114<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_Sun<br />
|1.0<br />
|"protein-dna"<br />
|pending publication<br />
|date<br />
|54,595<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_TCGA<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|date<br />
|number<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_TCGA<br />
|2.0<br />
|protein-protein (post-translational)<br />
|pending publication<br />
|date<br />
|number<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.hprd.org/ HPRD]<br />
|8.0<br />
|"protein-protein"<br />
|open<br />
|date<br />
|44,428<br />
|Data source<br />
<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://www.ebi.ac.uk/intact IntAct]<br />
|2.0.0<br />
|Interaction Types<br />
|not ready<br />
|date<br />
|number<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://mint.bio.uniroma2.it MINT]<br />
|2.6<br />
|protein-protein<br />
|not ready<br />
|date<br />
|number<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.reactome.org/ Reactome]<br />
|31<br />
|Interaction Types<br />
|open<br />
|date<br />
|number<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|}<br />
<br />
==Local abbreviations used==<br />
<br />
* '''BCi''' - B-Cell interactome, produced by an ARACNe run on B-Cell microarray data from the lab of Dr. Ricardo Dalla-Favera.<br />
* '''HGi''' - Human High-Grade Glioma interactome, produced by analysis of microarray data from several sources:<br />
** '''Phillips''' - data published by Phillips et al. ...<br />
** '''Sun''' - data published by Sun et al. ...<br />
** '''TCGA''' - data obtained from The Cancer Genome Atlas project (NCI).<br />
<br />
<br />
==Notes==<br />
<br />
* '''HGi version 1.0''' - interactome derived from ARACNe runs (transcriptional).<br />
* '''HGi version 2.0''' - interactome derived from a MINDy run (TCGA data only) (post-translational).</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=CNKB_Data&diff=6617CNKB Data2010-06-18T21:19:21Z<p>Mhonig: </p>
<hr />
<div>The Cellular Networks Knowledge Base (CNKB) component in geWorkbench 2.0.0 lists the following interactomes for query. However, some data has not yet be released and is password protected, and other data sets are not yet ready for query.<br />
<br />
Data that is currently available for query is shown in light green.<br />
<br />
==CNKB Data Summary==<br />
<br />
{| border="1" cellpadding="5" cellspacing="0" style="margin:10px;"<br />
|-style="color:black;background-color:#AAFFAA;"<br />
!Name<br />
!Version<br />
!Interaction Types<br />
!Availability<br />
!Date of release<br />
!Number of interactions<br />
!Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|BCi<br />
|1.0<br />
|"protein-dna"<br />
|open<br />
|date<br />
|41,727<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://thebiogrid.org/ BioGRID] <br />
|2.0.61<br />
|"protein-protein"<br />
|open<br />
|date<br />
|178,546<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://dip.doe-mbi.ucla.edu DIP]<br />
|2.4<br />
|"physical interaction","direct interaction","physical association","covalent binding","association","deacetylation reaction","acetylation reaction","phosphorylation reaction","dephosphorylation reaction"<br />
|not ready<br />
|date<br />
|39,412<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|Geneways<br />
|6.0<br />
|"protein-protein"<br />
|open<br />
|date<br />
|26,931<br />
|Rzhetsky lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_Phillips<br />
|1.0<br />
|protein-DNA (transcriptional)<br />
|open<br />
|date<br />
|number<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_Sun<br />
|1.0<br />
|protein-DNA (transcriptional)<br />
|pending publication<br />
|date<br />
|number<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_TCGA<br />
|1.0<br />
|protein-DNA (transcriptional)<br />
|open<br />
|date<br />
|number<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_TCGA<br />
|2.0<br />
|protein-protein (post-translational)<br />
|pending publication<br />
|date<br />
|number<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.hprd.org/ HPRD]<br />
|8.0<br />
|Interaction Types<br />
|open<br />
|date<br />
|number<br />
|Data source<br />
<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://www.ebi.ac.uk/intact IntAct]<br />
|2.0.0<br />
|Interaction Types<br />
|not ready<br />
|date<br />
|number<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://mint.bio.uniroma2.it MINT]<br />
|2.6<br />
|protein-protein<br />
|not ready<br />
|date<br />
|number<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.reactome.org/ Reactome]<br />
|31<br />
|Interaction Types<br />
|open<br />
|date<br />
|number<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|}<br />
<br />
==Local abbreviations used==<br />
<br />
* '''BCi''' - B-Cell interactome, produced by an ARACNe run on B-Cell microarray data from the lab of Dr. Ricardo Dalla-Favera.<br />
* '''HGi''' - Human High-Grade Glioma interactome, produced by analysis of microarray data from several sources:<br />
** '''Phillips''' - data published by Phillips et al. ...<br />
** '''Sun''' - data published by Sun et al. ...<br />
** '''TCGA''' - data obtained from The Cancer Genome Atlas project (NCI).<br />
<br />
<br />
==Notes==<br />
<br />
* '''HGi version 1.0''' - interactome derived from ARACNe runs (transcriptional).<br />
* '''HGi version 2.0''' - interactome derived from a MINDy run (TCGA data only) (post-translational).</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=CNKB_Data&diff=6616CNKB Data2010-06-18T21:10:08Z<p>Mhonig: </p>
<hr />
<div>The Cellular Networks Knowledge Base (CNKB) component in geWorkbench 2.0.0 lists the following interactomes for query. However, some data has not yet be released and is password protected, and other data sets are not yet ready for query.<br />
<br />
Data that is currently available for query is shown in light green.<br />
<br />
==CNKB Data Summary==<br />
<br />
{| border="1" cellpadding="5" cellspacing="0" style="margin:10px;"<br />
|-style="color:black;background-color:#AAFFAA;"<br />
!Name<br />
!Version<br />
!Interaction Types<br />
!Availability<br />
!Date of release<br />
!Number of interactions<br />
!Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|BCi<br />
|1.0<br />
|protein-DNA (transcriptional), protein-dna<br />
|open<br />
|date<br />
|41,727<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://thebiogrid.org/ BioGRID] <br />
|2.0.61<br />
|protein-protein<br />
|open<br />
|date<br />
|178,546<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://dip.doe-mbi.ucla.edu DIP]<br />
|2.4<br />
|protein-protein<br />
|not ready<br />
|date<br />
|number<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|Geneways<br />
|6.0<br />
|Interaction Types<br />
|open<br />
|date<br />
|number<br />
|Rzhetsky lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_Phillips<br />
|1.0<br />
|protein-DNA (transcriptional)<br />
|open<br />
|date<br />
|number<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_Sun<br />
|1.0<br />
|protein-DNA (transcriptional)<br />
|pending publication<br />
|date<br />
|number<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|HGi_TCGA<br />
|1.0<br />
|protein-DNA (transcriptional)<br />
|open<br />
|date<br />
|number<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|HGi_TCGA<br />
|2.0<br />
|protein-protein (post-translational)<br />
|pending publication<br />
|date<br />
|number<br />
|Califano lab<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.hprd.org/ HPRD]<br />
|8.0<br />
|Interaction Types<br />
|open<br />
|date<br />
|number<br />
|Data source<br />
<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://www.ebi.ac.uk/intact IntAct]<br />
|2.0.0<br />
|Interaction Types<br />
|not ready<br />
|date<br />
|number<br />
|Data source<br />
<br />
|-style="color:black;background-color:#FFFFFF;"<br />
|[http://mint.bio.uniroma2.it MINT]<br />
|2.6<br />
|protein-protein<br />
|not ready<br />
|date<br />
|number<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|[http://www.reactome.org/ Reactome]<br />
|31<br />
|Interaction Types<br />
|open<br />
|date<br />
|number<br />
|Data source<br />
<br />
|-style="color:black;background-color:#CCFFCC;"<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|align="center"|&mdash;<br />
|}<br />
<br />
==Local abbreviations used==<br />
<br />
* '''BCi''' - B-Cell interactome, produced by an ARACNe run on B-Cell microarray data from the lab of Dr. Ricardo Dalla-Favera.<br />
* '''HGi''' - Human High-Grade Glioma interactome, produced by analysis of microarray data from several sources:<br />
** '''Phillips''' - data published by Phillips et al. ...<br />
** '''Sun''' - data published by Sun et al. ...<br />
** '''TCGA''' - data obtained from The Cancer Genome Atlas project (NCI).<br />
<br />
<br />
==Notes==<br />
<br />
* '''HGi version 1.0''' - interactome derived from ARACNe runs (transcriptional).<br />
* '''HGi version 2.0''' - interactome derived from a MINDy run (TCGA data only) (post-translational).</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=FAQ&diff=4913FAQ2009-06-12T20:29:09Z<p>Mhonig: </p>
<hr />
<div>__NOEDITSECTION__<br />
=== Using geWorkbench ===<br />
<br />
====Q. How can I run geWorkbench on a 64-bit Windows system (or other system for which no installer currently is distributed)?====<br />
<br />
A. We have created a Zip file version of the geWorkbench distribution. It can be used on any operating system supporting Java, including 64 bit systems. Instructions are found on the geWorkbench releases notes at the GForge distribution site: https://gforge.nci.nih.gov/frs/?group_id=78<br />
<br />
====Q. I get a Java error when I try to start geWorkbench.====<br />
<br />
A. This is almost always caused by the Sun Java 1.5 JRE not being installed or not being found. Try reinstalling the Java 1.5 JRE and then reinstall geWorkbench. geWorkbench must be installed after the JRE.<br />
<br />
====Q. Where can I obtain the latest annotation files for my microarray platform?====<br />
A. Affymetrix annotation files can be downloaded from their support site, at www.affymetrix.com: Support->Technical Documentation->Annotation Files ([http://www.affymetrix.com/support/technical/annotationfilesmain.affx])<br />
<br />
====Q. How do I increase the amount of memory available to Java to run geWorkbench?====<br />
A. It depends on how you are running geWorkbench.<br />
<br />
1. If you are running a packaged distribution of geWorkbench (created using InstallAnywhere), there is a file in the geWorkbench root directory called UILauncher.lax. There is a line there which specifies the Java heap size:<br />
<br />
'''lax.nl.java.option.java.heap.size.max=640678989'''<br />
<br />
Here it is shown set to about 640 MB. You can experiment with increasing this, subject to the amount of memory in your machine and demands on it from other applications.<br />
<br />
2. If you are running geWorkbench from the source distribution using Ant, you can edit the build.xml file found in the geWorkbench root directory to alter the memory requested using the variable '''jvmarg''':<br />
<br />
<target name="run" depends="init" description="Runs geWorkbench."><br />
<java fork="true" classname="org.geworkbench.engine.config.UILauncher"><br />
<jvmarg value="-Xmx512M"/><br />
<jvmarg value="-Djava.library.path=lib"/><br />
<arg value="all_release.xml"/><br />
<classpath refid="run.classpath"/><br />
</java><br />
</target><br />
<br />
Here it is shown requesting 512 MB.<br />
<br />
<br />
====Q. How can I run ARACNE?====<br />
<br />
A. A new, Java-based version of ARACNE has been implemented and was released in geWorkbench v1.5.0. <br />
<br />
An earlier, standalone version of ARACNE is also availabe at http://amdec-bioinfo.cu-genome.org/html/ARACNE.htm<br />
<br />
<br />
<br />
<br />
====Q. How can I download the geWorkbench source?====<br />
<span id="download_geworkbench_code"></span><br />
A. You can download the development version from the GForge site (http://gforge.nci.nih.gov/scm/?group_id=78). There are two methods by which this can be done<br />
# Use the "Nightly CVS Tree Snapshot" link, or<br />
# Use anonymous CVS.<br />
<br />
<br />
Using the Nightly CVS Tree:<br />
<br />
# Click on the SCM tab.<br />
# Click on the link titled "Download The Nightly CVS Tree Snapshot" to download the whole code tree (warning: this is a big zip file).<br />
# Unzip and go to the top directory of the distribution.<br />
# Execute the script launch_geworkbench.sh or launch_geworkbench.bat (Windows). <br />
<br />
<br />
If you are familiar with CVS, you can obtain the source via an anonymous CVS download. You will need the following parameters for CVS.<br />
<br />
# username: anonymous<br />
# password: anonymous<br />
# protocol: ext<br />
# CVS server: cbiocvs2.nci.nih.gov:<br />
# CVSROOT directory: /cvsshare/content/gforge/geworkbench<br />
# CVS module name: geworkbench<br />
<br />
<br />
Whichever method is used, this is a source distribution which you will need to compile yourself:<br />
* you must have the Java JDK 5 (or higher) installed on your machine - see http://java.sun.com, under the "Java SE" link. <br />
* you must make sure that the value of the environment variable JAVA_HOME is the directory where the JDK is installed.<br />
<br />
Note that Sun recommends adding the Java JDK bin directory to your machine's PATH variable. Under Windows, "Typically this full path looks something like C:\Program Files\Java\jdk1.5.0_<version>\bin." Full instructions can be found on the Java site.<br />
<br />
If you have Ant installed on your machine, you can just type "ant run" in the geworkbench root directory and the program will be built and run. Ant can be downloaded from http://ant.apache.org/. Note that installing Ant involves manually adding the Ant bin directory to the PATH variable, setting the ANT_HOME directory, and optionally setting the JAVA_HOME directory.<br />
<br />
If you do not have Ant, you can just execute one of the provided launch scripts, also found the in geworkbench root directory. They are:<br />
* Windows: launch_geworkbench.bat<br />
* Linux/Unix/Mac: launch_geworkbench.sh<br />
<br />
====Q. How can I reference geWorkbench in a publication?====<br />
A. You can use the following statement: <br />
::"Analysis was carried out using geWorkbench (http://www.geworkbench.org), a free open source genomic analysis platform developed at Columbia University with funding from the NIH Roadmap Initiative (1U54CA121852-01A1) and the National Cancer Institute".<br />
<br />
<br />
====Q. ARACNE does not run in version 1.0.4 (Note that this version has been superseded).====<br />
<br />
A. There were two text files that were omitted from the distribution, you can download them from the [[Tutorial_-_ARACNE|ARACNE tutorial]] page and install them into the geWorkbench root directory.</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Home&diff=4912Home2009-06-12T20:27:42Z<p>Mhonig: </p>
<hr />
<div><b>geWorkbench</b> version 1.6.3 was released on January 8, 2009. Version 1.6.3 improves connectivity with caArray. We recommend that all users upgrade to the latest version. The release notes and downloads can be obtained from https://gforge.nci.nih.gov/frs/?group_id=78, and further instructions can be found on the [http://wiki.c2b2.columbia.edu/workbench/index.php/Download Download and Installation] page of this Wiki.<br />
<br />
<br />
'''geWorkbench''' (<u>ge</u>nomics <u>Workbench</u>) is a Java-based open-source platform for integrated genomics. Using a component architecture it allows individually developed plug-ins to be configured into complex bioinformatic applications. At present there are more than 50 available [[Plugins|plug-ins]] supporting the visualization and analysis of gene expression and sequence data. Example use cases include:<br />
* loading data from local or remote data sources.<br />
* visualizing gene expression, molecular interaction networks, protein sequence and protein structure data in a variety of ways.<br />
* providing access to client- and server-side computational analysis tools such as t-test analysis, hierarchical clustering, self organizing maps, regulatory neworks reconstruction, BLAST searches, pattern/motif discovery, etc.<br />
* validating computational hypothesis through the integration of gene and pathway annotation information from curated sources as well as through Gene Ontology enrichment analysis.<br />
<br/><br />
geWorkbench is the Bioinformatics platform of [http://magnet.c2b2.columbia.edu MAGNet], the '''National Center for the Multi-scale Analysis of Genomic and Cellular Networks''' (one of the [http://www.ncbcs.org 7 National Centers for Biomedial Computing] funded through the [http://nihroadmap.nih.gov/ NIH Roadmap]). Additionally, geWorkbench is supported by [https://cabig.nci.nih.gov/ caBIG™, NCI's cancer Biomedical Informatics Grid initiative].<br />
<br />
<br/><br />
End-user and developer support for geWorkbench is provided through the caBIG™ [https://cabig-kc.nci.nih.gov/Molecular/KC/index.php/Main_Page Molecular Analysis Tools Knowledge Center], a component of the caBIG™ [https://cabig.nci.nih.gov/esn/ Enterprise Support Network].<br />
<br />
<!--Many [[Magnet components|more components]] are scheduled for development in the context of the Center's activities.--><br />
<br />
<!--<br />
geWorkbench builds on [http://amdec-bioinfo.cu-genome.org/html/caWorkBench3.htm caWorkbench] (<u>ca</u>ncer <u>Workbench</u>), a project funded by the [http://www.cancer.gov/ National Cancer Institute (NCI)] and the [http://www.amdec.org/ Academic Medical Development Company (AMDeC)].<br />
--></div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=TestRestricted&diff=3814TestRestricted2006-11-14T03:41:22Z<p>Mhonig: </p>
<hr />
<div>Does this appear in the restricted pages list?</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=User:Mhonig&diff=3813User:Mhonig2006-11-14T03:39:37Z<p>Mhonig: </p>
<hr />
<div>Testing Restriction page</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Color_Mosaic_Design&diff=3796Color Mosaic Design2006-10-19T17:55:16Z<p>Mhonig: </p>
<hr />
<div>__NOEDITSECTION__<br />
=== Plugin Type ===<br />
<br />
The Color Mosaic Panel is a ''Visualization'' plugin.<br />
<br />
=== Data Sets ===<br />
<br />
The Color Mosaic Panel renders ''DSMicroarraySet'' and ''DSSignificanceResultSet'' data sets. It does not create any data sets.<br />
<br />
=== Subscribed Types ===<br />
<br />
The Color Mosaic Panel subscribes to the following types:<br />
<br />
# '''ProjectEvent''' - Receives data sets from the Project Panel.<br />
# '''AssociationPanelEvent''' - Receives p-values associated with the markers of a microarray set via this event.<br />
# '''PhenotypeSelectorEvent''' - Notifies the plugin of a change to Phenotype selection.<br />
# '''GeneSelectorEvent''' - Notifies the plugin of a change to Gene selection.<br />
<br />
=== Published Types ===<br />
<br />
# '''MarkerSelectedEvent''' - Published when a marker is selected in the visualization.<br />
# '''ImageSnapshotEvent''' - Published when an image snapshot is requested for the plugin.<br />
<br />
=== Description ===<br />
<br />
The Color Mosaic displays a heat map of a microarray set. Microarrays are displayed in the columns, and markers are displayed in the rows. It can render the entire set, or subset of markers and microarrays can be rendered. Active phenotype and gene selections are labelled in the color mosaic. If the result of T-Test or similar significance test is visualized, the associated p-values can also be included in the display.</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=.GEAR_files&diff=3792.GEAR files2006-10-13T21:25:39Z<p>Mhonig: </p>
<hr />
<div>__NOEDITSECTION__<br />
{{DevelopersTopNav}}<br />
<br />
<br />
== Overview ==<br />
<br />
.GEAR files are essentially zipped versions of geWorkBench visual plugins. They make it easy to distribute reasonably sized upgrades to specific parts of the application. They are the geWorkbench analogue of .WAR files for web applications.<br />
<br />
== Creating a .GEAR file ==<br />
<br />
There is an ant task that will create a .GEAR file automatically. Run ant with “ant –Dcomponent=NAME” which will create a .gear file from the specified component directory. You can also run the Windows batch file “makeGear NAME” instead. Put the resulting .gear file in the components directory of a geWorkbench installation and it will be loaded by the application.<br />
<br />
== Viewing loaded versions of components ==<br />
<br />
The version menu item, under help will list all the loaded versions of plugins, and will indicate which ones are loading from .GEAR files, an example is below.<br />
<br />
[[Image:VersionDialog.png||Example version screen.]]</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Tutorials&diff=3722Tutorials2006-09-22T23:59:25Z<p>Mhonig: </p>
<hr />
<div>__NOEDITSECTION__<br />
{{TutorialsTopNav}}<br />
<br />
<br />
The tutorials shown on this page provide a quick introduction to the most important features of geWorkbench. Additional information can be found in the User Guide (in preparation) and in the Online Help section of the program. <br />
<br />
All data sets used in the tutorials are available from the [[Download#Tutorial_data | download area]] of our site.<br />
<br />
<br />
<br />
===[[Tutorial - Getting_Started | Getting Started]]===<br />
Obtaining and installing geWorkbench. Requirements.<br />
<br />
===[[Tutorial - Basics | Basics]]===<br />
A brief introduction to the use of geWorkbench.<br />
<br />
===[[Tutorial - Projects and Data Files | Projects and Data Files]]===<br />
Creating projects, loading microarray data files, merging into one dataset, and saving.<br />
<br />
===[[Tutorial - Data Subsets | Data Subsets]]===<br />
Subsets of both markers and arrays can be defined for targeted analysis.<br />
<br />
===[[Tutorial - Viewing a Microarray Dataset | Viewing a Microarray Dataset]]===<br />
Survey of geWorkbench visusaliztion tools for microarray data.<br />
<br />
===[[Tutorial - Filtering and Normalizing | Filtering and Normalizing]]===<br />
geWorkbench provides numerous methods for filtering and normalizing microarray data.<br />
<br />
===[[Tutorial - Differential Expression | Differential Expression]]===<br />
Several variants of the t-test are available.<br />
<br />
===[[Tutorial - Clustering | Clustering]]===<br />
Data can be clustered using a fast hierarchical clustering routine, as well as SOMs.<br />
<br />
===[[Tutorial - Marker Annotations | Marker Annotations]]===<br />
Marker annotations can be retrieved, including BioCarta pathway diagrams.<br />
<br />
===[[Tutorial - Sequence Retrieval | Sequence Retrieval]]===<br />
Genomic sequences for markers can be retrieved for further analysis.<br />
<br />
===[[Tutorial - BLAST | BLAST]]===<br />
geWorkbench can run BLAST jobs on the JCSB cluster.<br />
<br />
===[[Tutorial - Pattern Discovery | Pattern Discovery]]===<br />
Upstream seqeunce can be analyzed for conserved sequence patterns.<br />
<br />
===[[Tutorial - Promoter Analysis | Promoter Analysis]]===<br />
Search a set of sequences against a promoter database.<br />
<br />
===[[Tutorial - Reverse Engineering | Reverse Engineering]]===<br />
Simple network reverse engineering - microarray datasets can be analyzed for interactions between genes.<br />
<br />
===[[Tutorial - ARACNE | ARACNE]]===<br />
Formal method for reverse Engineering - microarray datasets can be analyzed for interactions between genes.<br />
<br />
===[[Tutorial - Network Browser| Network Browser]]===<br />
Provides visualization of adjacency matrix generated by ARACNE, using Cytoscape.<br />
<br />
===[[Tutorial - GO Term Enrichment | GO Term Enrichment]]===<br />
Determine if particluar Gene Ontology terms are overrepresented in a data subset.<br />
<br />
===[[Tutorial - Synteny | Synteny]]===<br />
Compare genomic sequence from two different species.<br />
<br />
<br />
('''NOTE''': This section of our web site is under active development. More tutorials are forthcoming, covering many usage scenarios for geWorkbench.)</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Tutorial_-_Getting_Started&diff=3689Tutorial - Getting Started2006-09-22T16:48:46Z<p>Mhonig: Tutorials - Getting Started moved to Tutorial - Getting Started</p>
<hr />
<div>{{TutorialsTopNav}}<br />
<br />
==Versions available:==<br />
Downloads are available for current versions of Windows, Linux and Macintosh OS-X. Our primary development and testing platform is Windows XP.<br />
<br />
<br />
==Requirements:==<br />
<br />
===Java:===<br />
geWorkbench requires that a version of the Sun Java Runtime Environment 5.0 or higher be installed on your computer. (This is also known as JRE version 1.5). The JRE is available at [http://java.sun.com/j2se/1.5.0/download.jsp J2SE 5.0].<br />
<br />
===Memory:===<br />
Testing of geWorkbench is done on machines with 1 GB of memory. 512 MB should be adequate for most geWorkbench modules. Working with large datasets (100s of arrays) may require additional memory. <br />
<br />
In version 1.0.4, the Hierachical Clustering tutorial requires a machine with 1 GB of memory, and the Java heap size must be set to at least 450 MB. This can be done in the file '''UILauncher.lax''' which is found in the application root directory of the InstallAnywhere packaged versions of geWorkbench. Specifically, the following line in that file should be set as follows:<br />
<br />
lax.nl.java.option.java.heap.size.max=450678989<br />
<br />
<br />
<br />
==Installation:==<br />
<br />
See the Download menu at left to obtain geWorkbench. The self-installing file includes all currently available geWorkbench modules as well as several example data files.<br />
The download package is created using InstallAnywhere from ZeroG Software.</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Tutorials_-_Getting_Started&diff=3690Tutorials - Getting Started2006-09-22T16:48:46Z<p>Mhonig: Tutorials - Getting Started moved to Tutorial - Getting Started: revert</p>
<hr />
<div>#redirect [[Tutorial - Getting Started]]</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Tutorial_-_Getting_Started&diff=3687Tutorial - Getting Started2006-09-22T16:45:13Z<p>Mhonig: Tutorial - Getting Started moved to Tutorials - Getting Started</p>
<hr />
<div>{{TutorialsTopNav}}<br />
<br />
==Versions available:==<br />
Downloads are available for current versions of Windows, Linux and Macintosh OS-X. Our primary development and testing platform is Windows XP.<br />
<br />
<br />
==Requirements:==<br />
<br />
===Java:===<br />
geWorkbench requires that a version of the Sun Java Runtime Environment 5.0 or higher be installed on your computer. (This is also known as JRE version 1.5). The JRE is available at [http://java.sun.com/j2se/1.5.0/download.jsp J2SE 5.0].<br />
<br />
===Memory:===<br />
Testing of geWorkbench is done on machines with 1 GB of memory. 512 MB should be adequate for most geWorkbench modules. Working with large datasets (100s of arrays) may require additional memory. <br />
<br />
In version 1.0.4, the Hierachical Clustering tutorial requires a machine with 1 GB of memory, and the Java heap size must be set to at least 450 MB. This can be done in the file '''UILauncher.lax''' which is found in the application root directory of the InstallAnywhere packaged versions of geWorkbench. Specifically, the following line in that file should be set as follows:<br />
<br />
lax.nl.java.option.java.heap.size.max=450678989<br />
<br />
<br />
<br />
==Installation:==<br />
<br />
See the Download menu at left to obtain geWorkbench. The self-installing file includes all currently available geWorkbench modules as well as several example data files.<br />
The download package is created using InstallAnywhere from ZeroG Software.</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Known_Issues&diff=3686Known Issues2006-09-22T16:35:49Z<p>Mhonig: </p>
<hr />
<div>none at the moment ...</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=FAQ&diff=3679FAQ2006-09-20T20:45:45Z<p>Mhonig: </p>
<hr />
<div>__NOEDITSECTION__<br />
==== Using geWorkbench ====<br />
<br />
Q. I get a Java error when I try to start geWorkbench.<br />
<br />
A. This is almost always caused by the Sun Java 1.5 JRE not being installed or not being found. Try reinstalling the Java 1.5 JRE and then reinstall geWorkbench. geWorkbench must be installed after the JRE.<br />
<br />
<br />
Q. ARACNE does not run in version 1.0.4<br />
<br />
A. There are two text files that were omitted from the distribution, you can download them from the [[Tutorial_-_ARACNE|ARACNE tutorial]] page and install them into the geWorkbench root directory.<br />
<br />
<br />
Q. Pattern Discovery does not run in version 1.0.4<br />
<br />
A. A new build is being created to fix this. Watch for version 1.0.5.<br />
<br />
==== Development ====</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Plugins&diff=3678Plugins2006-09-20T20:45:05Z<p>Mhonig: </p>
<hr />
<div>__NOEDITSECTION__<br />
The geWorkbench platform employs a component repository infrastructure to manage a large collection of pluggable components that can be used to customize the application's graphical user interface. This (ever growing) list of plug-in components covers a wide range of fucntionality for a number of different genomic data modalities.<br />
<br />
<br />
<br />
__TOC__<br />
<br />
==Microarray Visualization==<br />
{|style="border: 1px solid lightGray"<br />
!Plugin||Description<br />
|-<br />
|-<br />
|width="150"|Color Mosaic||Heat maps for microarray expression data, organized by phenotypic or gene groupings ([[media:Color-mosaic.png|screenshot]]).<br />
|-<br />
|-<br />
<br />
|width="150"|Dendrogram||Tree-structured diagrams reflecting the results of hierarchical clustering analysis ([[media:Dendrogram.png|screenshot]]).<br />
|-<br />
|-<br />
|width="150"|Expression Profiles||Line graph of genes expression profiles across several arrays/ hybridizations ([[media:Expression-profile.png|screenshot]]).<br />
|- <br />
|-<br />
|width="150"|Expression Value Distribution||Distribution plot of marker expression values across one or more microarrays.<br />
|-<br />
|-<br />
<br />
|width="150"|Microarray Viewer||Color-gradient representation of gene expression values ([[media:Microarray-panel.png|screenshot]]).<br />
|- <br />
|-<br />
<br />
|width="150"|Scatter Plot || Pairwise (array vs. array and marker vs. marker) comparison and plotting of expression values ([[media:Scatterplot.png|screenshot]]).<br />
|- <br />
|-<br />
<br />
|width="150"|SOM Clusters Viewer ||Visualization of gene clusters produced by the self-organizing maps analysis ([[media:Somcluster.png|screenshot]]). <br />
|- <br />
|-<br />
<br />
|width="150"|Tabular Microarray Viewer|| Spreadsheet view of all expression measurement in an experiment, one row per individual marker/probe and one column per microarray ([[media:Tabular.png|screenshot]]).<br />
|-<br />
|}<br />
<br />
==Data Management==<br />
{|style="border: 1px solid lightGray"<br />
!Plugin||Description<br />
|- <br />
|-<br />
|width="150"|Marker Component ||Definition of data views consisting of marker subgroups. The views control the amount of data displayed.<br />
|- <br />
|-<br />
|width="150"|Phenotype/Array Component ||Definition of data views consisting of microarray subgroups. The views control the amount of data displayed.<br />
|-<br />
|-<br />
|}<br />
<br />
==Normalizers==<br />
{|style="border: 1px solid lightGray"<br />
!Plugin||Description<br />
|-<br />
|width="150"|Array-Based Centering||Subtraction of the mean or median measurement of a microarray from every measurement in that microarray.<br />
|-<br />
|-<br />
|width="150"|Marker-Based Centering||Subtraction of the mean or median measurement of a marker profile from every measurement in the profile.<br />
|-<br />
|-<br />
|width="150"|Mean-Variance Normalizer||Transformation of expression measurements to standard units: for every marker, the mean measurement of the marker profile (across all microarrays in an experiment) is subtracted from each measurement in the profile and the resulting value is divided by the standard deviation of the profile.<br />
|-<br />
|-<br />
|width="150"|Missing Value Calculation||Replacement of missing values with consensus values.<br />
|-<br />
|-<br />
|width="150"|Threshold Normalizer ||Adjustment of values that fall outside a user-specified threshold.<br />
|-<br />
|width="150"|Quantile || Expression measurements in each microarray are adjusted so that the distribution of values is the same across all microarrays in an experiment.<br />
|-<br />
|-<br />
|width="150"|Housekeeping || Normalization of all measurements in a microarray through division by the average expression value of a (user defined) set of housekeeping genes.<br />
|-<br />
|}<br />
<br />
== Filters==<br />
<br />
{|style="border: 1px solid lightGray"<br />
!Plugin||Description<br />
|-<br />
|-<br />
|width="150"|Affy Detection Call||(''Affymetrix data only)'' Filtering of measurements based on the value of their "detection call" attribute.<br />
|-<br />
|-<br />
|width="150"|Deviation|| Filtering of markers with low dynamic range.<br />
|-<br />
|-<br />
|width="150"|Expression Threshold|| Elimination of measurements that fall outside a range of explression values.<br />
|-<br />
|-<br />
|width="150"|2-channel Threshold||(''Genepix data only)'' Same as "Expression Threshold" filter but different threshold ranges can be specified for each channel.<br />
|-<br />
|-<br />
|width="150"|Genepix Flag Filter|| ''(Genepix data only)'' Filtering of measurements based on the value of their "Flags" attribute.<br />
|-<br />
|}<br />
<br />
<br />
==Annotation==<br />
<br />
{|style="border: 1px solid lightGray"<br />
!Plugin||Description<br />
|-<br />
|width="150"|Dataset History||Log of data transformations induced by data-modifying operations.<br />
|-<br />
|-<br />
|width="150"|Dataset Annotation||Free text format box used to annotate data, images and results. Such annotations persist application invocations and can be used as an online "lab notebook".<br />
|-<br />
|-<br />
|width="150"|Experiment Information||Microarray machine parameters used in an experiment run. If available, high-level experiment information (e.g., purpose of of experiment) are also displayed.<br />
|-<br />
|-<br />
|width="150"|Marker Annotations||Retrieval of gene and pathway information for markers on a microarray.<br />
|-<br />
|-<br />
|width="150"|caBIO Pathway Listing||Visualization of BioCarta pathway diagrams ([[media:Cabiopathway.png|screenshot]]).<br />
|-<br />
|width="150"|Gene Ontology||Enrichment analysis of selected groups of genes against Gene Ontology (http://www.geneontology.org) annotations ([[media:Go_Terms_Panel.png|screenshot]]).<br />
|-<br />
|-<br />
|}<br />
<br />
==Network Generation==<br />
<br />
{|style="border: 1px solid lightGray"<br />
!Plugin||Description<br />
|-<br />
|width="150"|ARACNE Reverse Engineering|| Analysis of large amount of microarray data (typically 100-500 microarrays) to reverse engineer underlying gene regulatory networks ([[media:Reverseengineering.png|screenshot]]).<br />
|-<br />
|-<br />
|-<br />
|width="150"|Cytoscape||Visualization of gene regulatory network created in Reverse Engineering using [http://www.cytoscape.org/ Cytoscape 2.0]([[media:Cytoscape.png|screenshot]]).<br />
|-<br />
|}<br />
<br />
==Analysis==<br />
<br />
{|style="border: 1px solid lightGray"<br />
!Plugin||Description<br />
|-<br />
|width="150"|Hierarchical Clustering||Clustering of markers and microarrays into hierarchical binary trees. The resulting structures can be visualized in the Dendrogram plugin.<br />
|-<br />
|-<br />
|width="150"|Self Organizing Map (SOM)|| Clustering of markers using self organizing maps. The resulting clusters can be visualized in the SOM Clusters Viewer plugin.<br />
|-<br />
|-<br />
|width="150"|T Test||Identification of markers with statistically significant differential expression between sets of microarrays. T-testing is used for the determination of significance ([[media:Volcanoplot.png|screenshot]]).<br />
|-<br />
<br />
|}<br />
<br />
== Sequence Analysis & Visualization ==<br />
{|style="border: 1px solid lightGray"<br />
!Plugin||Description<br />
|-<br />
|-<br />
|width="150"|Sequence Alignment||Server-based versions of BLAST and Smith-Waterman alignment ([[media:Synteny Blastresults.png|screenshot]]). <br />
|-<br />
|-<br />
|width="150"|Synteny|| Comparison of sequence similarity between two genomic regions. The comparison results are represented as a dot matrix augmented with detailed annotation for both regions ([[media:Synteny Dotmatrix.png|screenshot]]).<br />
|-<br />
|-<br />
|width="150"|Promoter Analysis||Identification of putative transcription factor binding sites in DNA sequences ([[media:Promoterpanel.png|screenshot]]). The analysis use the profiles in the [http://jaspar.cgb.ki.se/cgi-bin/jaspar_db.pl JASPAR Transcription Factor Binding Profile Database.]<br />
|-<br />
|-<br />
|width="150"|Pattern Discovery|| Discovery of sequence motifs in sets of DNA and protein sequences.<br />
|-<br />
|-<br />
|width="150"|Position Histogram || Visualization of results from the Pattern Discovery plugin. Motif/pattern support is plotted against relative sequence position of the motif match ([[media:Histogram.png|screenshot]]). <br />
|-<br />
|-<br />
|width="150"|Sequence Panel || Visualization of results from the Pattern Discovery plugin, displaying the motif match location over each sequence from the input data set.<br />
|-<br />
|}</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Download_and_Installation&diff=3677Download and Installation2006-09-20T20:44:26Z<p>Mhonig: </p>
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<div>__NOEDITSECTION__<br />
{{DownloadTopNav}}<br />
<br />
==Software Requirements==<br />
To run geWorkbench you will need to have '''Sun Java J2SE 5.0''' or higher installed on your computer (this is also refered to as the Java 1.5 JRE). If the JRE is not already installed on your computer you can get it from Sun's Java Web site, http://java.sun.com/j2se/1.5.0/download.jsp. geWorkbench is downloaded as a self-installing package with support for Windows, Linux and MAC OS-X.<br />
<br />
==Hardware Requirements==<br />
Testing of geWorkbench is done on machines with 1 GB of memory. 512 MB should be adequate for most geWorkbench modules. Working with large datasets (100s of arrays) may require additional memory. <br />
<br />
<br />
==IMPORTANT NOTICE ABOUT LICENSE==<br />
Use of geWorkbench is governed by the rules specified in the [[geWorkbench License | software license]]. Please make sure to read the license and understand your obligations before proceeding to download the application.<br />
<br />
<br />
==Downloads==<br />
<br />
Up to date versions of geWorkbench (current version -> 1.0.4, Friday August 18th, 2006) and the geWorkbench Software Development Kit (current version -> 1.0.1) can be downloaded from our project page at NCI's GForge repository:<br />
http://gforge.nci.nih.gov/frs/?group_id=78<br />
If you wish to receive announcements about new application and SDK releases please subscribe to the mailing list [http://gforge.nci.nih.gov/mailman/listinfo/geworkbench-announce geworkbench-announce@gforge.nci.nih.gov]. Other available mailing lists are described in the [[Community]] section of our site.<br />
<br />
==Installation Instructions==<br />
<br />
You must have the Java 1.5 JRE installed before installing geWorkbench.<br />
<br />
===Windows Instructions:===<br />
<br />
*After downloading, double-click geWorkbench_v1.0.4_Windows_installer.exe<br />
<br />
===Mac OS X Instructions:===<br />
<br />
*After downloading, double-click geworkbench_v1.0.4_Mac_installer.zip <br />
<br />
*Notes<br />
**Requires Mac OS X 10.4 or later<br />
**The compressed installer should be recognized by Stuffit Expander and should automatically be expanded after downloading. If it is not expanded, you can expand it manually using StuffIt Expander 6.0 or later.<br />
**If you have any problems launching the installer once it has been expanded, make sure that the compressed installer was expanded using Stuffit Expander.<br />
<br />
===Linux Instructions:===<br />
<br />
*After downloading open a shell and, cd to the directory where you downloaded the installer.<br />
*At the prompt type: sh ./geWorkbench_v1.0.4_Linux_installer.bin<br />
<br />
==Tutorial data==<br />
<br />
[[Media:tutorial_data.zip|tutorial_data.zip]] (3.586 MB) - data files in several different formats useful for the tutorials or just trying out geWorkbench.<br />
<br />
<br />
[[Media:webmatrix2.zip|webmatrix2.zip]] (5.647 MB) - a large (100 array) microarray dataset in the geWorkbench matrix format. Data is from the lab of Riccardo Dalla-Favera, Columbia University, and is provided only for use in learning and testing geWorkbench.</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Tutorials&diff=3676Tutorials2006-09-20T20:32:29Z<p>Mhonig: </p>
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{{TutorialsTopNav}}<br />
<br />
<br />
The tutorials shown on this page provide a quick introduction to the most important features of geWorkbench. Additional information can be found in the User Guide (in preparation) and in the Online Help section of the program. <br />
<br />
All data sets used in the tutorials are available from the [[Download#Tutorial_data | download area]] of our site.<br />
<br />
<br />
<br />
===[[Tutorial - Getting_Started | Getting Started]]===<br />
Obtaining and installing geWorkbench. Requirements.<br />
<br />
===[[Tutorial - Basics | Basics]]===<br />
A brief introduction to the use of geWorkbench.<br />
<br />
===[[Tutorial - Projects and Data Files | Projects and Data Files]]===<br />
Creating projects, loading microarray data files, merging into one dataset, and saving.<br />
<br />
===[[Tutorial - Data Subsets | Data Subsets]]===<br />
Subsets of both markers and arrays can be defined for targeted analysis.<br />
<br />
===[[Tutorial - Viewing a Microarray dataset | Viewing a Microarray Dataset]]===<br />
Survey of geWorkbench visusaliztion tools for microarray data.<br />
<br />
===[[Tutorial - Filtering and Normalizing | Filtering and Normalizing]]===<br />
geWorkbench provides numerous methods for filtering and normalizing microarray data.<br />
<br />
===[[Tutorial - Differential Expression | Differential Expression]]===<br />
Several variants of the t-test are available.<br />
<br />
===[[Tutorial - Clustering | Clustering]]===<br />
Data can be clustered using a fast hierarchical clustering routine, as well as SOMs.<br />
<br />
===[[Tutorial - Marker Annotations | Marker Annotations]]===<br />
Marker annotations can be retrieved, including BioCarta pathway diagrams.<br />
<br />
===[[Tutorial - Sequence Retrieval | Sequence Retrieval]]===<br />
Genomic sequences for markers can be retrieved for further analysis.<br />
<br />
===[[Tutorial - BLAST | BLAST]]===<br />
geWorkbench can run BLAST jobs on the JCSB cluster.<br />
<br />
===[[Tutorial - Pattern Discovery | Pattern Discovery]]===<br />
Upstream seqeunce can be analyzed for conserved sequence patterns.<br />
<br />
===[[Tutorial - Promoter Analysis | Promoter Analysis]]===<br />
Search a set of sequences against a promoter database.<br />
<br />
===[[Tutorial - Reverse Engineering | Reverse Engineering]]===<br />
Simple network reverse engineering - microarray datasets can be analyzed for interactions between genes.<br />
<br />
===[[Tutorial - ARACNE | ARACNE]]===<br />
Formal method for reverse Engineering - microarray datasets can be analyzed for interactions between genes.<br />
<br />
===[[Tutorial - Network Browser| Network Browser]]===<br />
Provides visualization of adjacency matrix generated by ARACNE, using Cytoscape.<br />
<br />
===[[Tutorial - GO Term Enrichment | GO Term Enrichment]]===<br />
Determine if particluar Gene Ontology terms are overrepresented in a data subset.<br />
<br />
===[[Tutorial - Synteny | Synteny]]===<br />
Compare genomic sequence from two different species.<br />
<br />
<br />
('''NOTE''': This section of our web site is under active development. More tutorials are forthcoming, covering many usage scenarios for geWorkbench.)</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Screenshots&diff=3675Screenshots2006-09-20T20:31:58Z<p>Mhonig: </p>
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== geWorkbench screenshots ==<br />
<br />
=== Microarray Panel ===<br />
The Microarray Panel displaying marker values for selected array.<br />
<br />
<br />
[[image:microarray-panel.png]]<br />
----<br />
<br />
=== Color Mosaic ===<br />
The Color Mosaic component displaying selected arrays, group designation and marker names.<br />
<br />
<br />
[[Image:color-mosaic.png]]<br />
----<br />
<br />
=== Expression Profile ===<br />
Expression Profile plotting values for selected markers and arrays.<br />
<br />
<br />
[[Image:expression-profile.png]]<br />
----<br />
<br />
=== Hierarchical Clustering ===<br />
A Dendrogram displays the results of the Hierarchical clustering analysis.<br />
<br />
<br />
[[Image:dendrogram.png]]<br />
----<br />
<br />
=== SOM Clustering ===<br />
Self Ordered Map clustering results are displayed as series of expression profiles corresponding to discovered groupings.<br />
<br />
<br />
[[Image:somcluster.png]]<br />
----<br />
<br />
=== Scatter Plot ===<br />
Compare multiple markers or arrays with the standard Scatter Plot analysis.<br />
<br />
<br />
[[Image:scatterplot.png]]<br />
----<br />
<br />
=== Volcano Plot ===<br />
The Volcano Plot shows the results of a T Test analysis.<br />
<br />
<br />
[[Image:volcanoplot.png]]<br />
----<br />
<br />
=== caBIO Pathway ===<br />
Using a connection to caBIO, pathway diagrams can be retrieved and displayed.<br />
<br />
<br />
[[Image:cabiopathway.png]]<br />
----<br />
<br />
=== Reverse Engineering ===<br />
Use the ARACNE algorithm to reverse engineer the underlying gene regulatory network.<br />
<br />
<br />
[[Image:reverseengineering.png]]<br />
----<br />
<br />
=== Cytoscape ===<br />
Use the Cytoscape network visualization to view the reverse engineered regulatory network.<br />
<br />
<br />
[[Image:cytoscape.png]]<br />
----<br />
<br />
=== Pattern Discovery ===<br />
Use the SPLASH algorithm to discover sparse amino or nucleic acid patterns in a loaded sequence.<br />
<br />
<br />
[[Image:patterndiscovery.png]]<br />
----<br />
<br />
=== Promoter Panel ===<br />
The Promoter Panel uses the JASPAR Transcription Factor Binding Profile Database to search for promoter regions in the loaded sequence.<br />
<br />
<br />
[[Image:promoterpanel.png]]<br />
----<br />
<br />
=== BLAST Queries ===<br />
The BLAST panel runs queries against the Paracel Blast machine running at the Columbia Genome Center.<br />
<br />
<br />
[[Image:blastresults.png]]<br />
----</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=Overview&diff=3674Overview2006-09-20T20:30:56Z<p>Mhonig: </p>
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<div>__NOEDITSECTION__<br />
==Introduction==<br />
<br />
geWorkbench is an open-source bioinformatics platform that offers a comprehensive and extensible collection of tools for the management, analysis, visualization and annotation of biomedical data. Many kinds of analysis are supported - for microarrays, there are filtering and normalization, basic statistical analyses, clustering, network reverse engineering, as well as many common visualization tools. For sequence data there are routines such as BLAST, pattern detection, transcription factor mapping, and syntenic region analysis. Furthermore, genomic sequences around markers of interest found in microarray experiments can be easily retrieved and, for example, used for promoter/transcription factor analysis.<br />
<br />
Specific types of data supported include:<br />
<br />
*Microarray Gene Expression<br />
**Affymetrix GCOS/MAS5<br />
**Matrix format (geWorkbench)<br />
**RMAExpress<br />
**GenePix<br />
*DNA and Protein Sequences<br />
**FASTA<br />
*Pathways<br />
**BioCarta<br />
*Patterns<br />
**Regular Expressions<br />
*Gene Ontology<br />
*Networks<br />
<br />
Most importantly, geWorkbench provides an environment which supports moving from one data type to another in a seamless fashion, e.g. from gene expression to sequences to patterns.<br />
<br />
[[Image:slide1.gif]]<br />
<br />
==Developing for geWorkbench==<br />
<br />
geWorkbench has been designed using a plug-in framework which allows new modules to be developed with relative ease. A repository will be maintained for community-developed modules. Developers can take advantage of all the existing capabilities for data management and visualization, and thus concentrate development efforts on the more important, novel aspects of their project.<br />
<br />
<br />
==geWorkbench as an interface to external data and computational resources==<br />
<br />
geWorkbench provides access to a variety of external data sources, including:<br />
*Microarray gene expression repositories (caArray)<br />
*Gene annotation pages (via CGAP)<br />
*DNA sequence retrieval<br />
*Pathway diagrams (BioCarta)<br />
<br />
geWorkbench also provides a gateway to several computational services currently hosted on Columbia servers and clusters, including:<br />
*BLAST<br />
*Pattern Discovery<br />
*Synteny<br />
<br />
<br />
==Basic Layout of the Graphical User Interface==<br />
<br />
<br />
The graphical user interface for geWorkbench is divided into four major sections, for<br />
<br />
1. Projects - Data management (upper left)<br />
<br />
2. Marker and Array/Phenotype set selection and management (lower left)<br />
<br />
3. Visualization tools (upper right)<br />
<br />
4. Analytical tools (lower right)<br />
<br />
<br />
[[Image:T_geWorkbench1.0_all.png]]<br />
<br />
<br />
The Data Management area can hold one workspace, and a workspace in turn can hold one or more projects. Projects can be used as wished to group different data sets. Each opened data file or analysis result is stored in a project. A workspace and all the data it contains can be saved and returned to later.<br />
<br />
The GUI provides a menu bar at top with a standard choice of commands. Many commands that are available in the menu bar are also available by right-clicking on data objects.</div>Mhonighttp://wiki.c2b2.columbia.edu/workbench/index.php?title=File:Test.txt&diff=3072File:Test.txt2006-05-15T14:51:51Z<p>Mhonig: </p>
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<div></div>Mhonig