Workflows

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

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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: Wei Tan Ravi Stian Soiland-Reyes

Using CQL to query protein sequence data (1)

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To query protein sequence infomation out of 3 caGrid data services: caBIO, CPAS and GridPIR Adapted from http://www.myexperiment.org/workflows/600

Created: 2009-05-07

Credits: Stian Soiland-Reyes

Attributions: Using CQL to query protein sequence data

An example workflow with WSRF service (1)

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An example workflow with WSRF service The service used is http://sidgrid.ci.uchicago.edu:8100/wsrf/services/CounterService The service is included in Globus toolkit installation (ws-core). If the it is down you can host your own and modify the workflow definition file to point to your own. The workflow first creates a counter instance and adds the value 10 for two times to the same counter. Therefore the result should be 20.

Created: 2009-07-28

Credits: Wei Tan Stian Soiland-Reyes

caArray data retrieving (1)

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Query all the gene expression data in a caArray experiment. Returns a evenly divided gene expression data set with corresponding class information. They ca be later used as training and test data set in many classification algorithms.Query all the gene expression data in a caArray experiment. Returns a evenly divided gene expression data set with corresponding class information. They can be later used as training and test data set in many classification algorithms.

Created: 2009-11-23

Credits: Wei Tan