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Workflow Fetch PDB flatfile from RCSB server (1)

Given an identifier such as '1crn' fetches the PDB format flatfile and returns the corresponding 3D image of the protein.

Created: 2008-03-05 | Last updated: 2008-03-31

Credits: User Tomoinn

Workflow A workflow version of the EMBOSS tutorial (1)

Designed to show the use of EMBOSS based Soaplab services from Taverna, this workflow has no inputs as all initial values are specified as string constants. A sequence set is fetched using the seqret tool, then simultaneously scanned for predicted transmembrane regions and subjected to a multiple alignment using emma. This alignment is then plotted to a set of PNG images and also used to build a profile using the prophecy and prophet tools.

Created: 2008-03-05 | Last updated: 2008-03-25

Credits: User Tomoinn

Workflow Multiple Blastp (2)

This is a workflow to automate multiple BLASTp jobs on a large list of protein sequences in FASTA format.

Created: 2007-11-20 | Last updated: 2008-01-10

Credits: User Kieren Lythgow

Workflow Image Mining with RapidMiner (1)

This is an image mining process using the image mining Web service provided by NHRF within e-Lico. It first uploads a set of images found in a directory, then preprocesses the images and visualizes the result. Furthermore, references to the uploaded images are stored in the local RapidMiner repository so they can later be used for further processing without uploading images a second time.

Created: 2010-04-28 | Last updated: 2012-01-16

Workflow Get weather information (3)

Get the weather forcast of the day for you city. Info display: wind, visibility, temperature, sky conditions and pressure. The default value Stian's home country.

Created: 2008-06-17 | Last updated: 2008-06-20

Credits: User Franck Tanoh User Stian Soiland-Reyes

Attributions: Workflow Get weather information Workflow Get cities by country name


Workflow Escherichia coli : From cDNA Microarray Ra... (1)

This workflow takes in a CDNA raw file and a normalisation method then returns a series of images/graphs which represent the same output obtained using the R and bioconductor. Also retruned by this workflow are a list of the top differentialy expressed genes (size dependant on the number specified as input - geneNumber), which are then used to find the candidate pathways which may be influencing the observed changes in the microarray data. By identifying the candidate pathways, more detailed...

Created: 2008-05-08 | Last updated: 2008-05-12

Credits: User Saeedeh User Paul Fisher

Attributions: Workflow HUMAN Microarray CEL file to candidate pathways

Workflow conditional branch (2)

Example of a conditional execution workflow. use 'false' or 'true' as input

Created: 2007-10-03


Workflow Lymphoma type prediction based on microar... (7)

Scientific value Using gene-expression patterns associated with DLBCL and FL to predict the lymphoma type of an unknown sample. Using SVM (Support Vector Machine) to classify data, and predicting the tumor types of unknown examples. Steps Querying training data from experiments stored in caArray. Preprocessing, or normalize the microarray data. Adding training and testing data into SVM service to get classification result.

Created: 2010-05-11 | Last updated: 2010-05-11

Credits: User Wei Tan User Ravi User Stian Soiland-Reyes

Workflow Workflow Pattern - Structured Loop (B) (2)

This workflow is an alternative GWorkflowDL representation of a structured loop that updates the variable "x" in each iteration and which models the control flow separately from the index "i". Here a version of the graph with manual graph layout: This workflow is equivalent to the following pseudo code: x:=0; for ( i:=0; i<=99; i++) { x:=x+i; } x_result:=x; Please remark that this demonstration workflow does not invoke any external services at all. The c...

Created: 2008-12-09

Credits: User Andreas Hoheisel

Attributions: Workflow Workflow Pattern - Structured Loop


Workflow Identification of differential genes using... (1)

This workflow starts by retrieving the names of microarray datasets from the Maxd database. The user has to select sets of control and test data which are then analysed by the LIMMA Bioconductor package in an R script. This produces a list of significant differentially expressed genes which is then analysed using the Go Term Finder tool to generate a PDF report of the common GO terms associated with the genes. A CSV file containing the list of sign...

Created: 2008-07-02 | Last updated: 2008-07-02

Credits: User Peter Li

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