]> caArray Experiment data: Diffuse large B-cell lymphoma outcome prediction 2009-04-23T00:00:00Z 2009-04-23T00:00:00Z 2009-04-23T17:51:56Z 2009-04-23T17:51:56Z 2008-07-07T19:35:32Z 2010-05-26T16:26:22Z Wei Tan Chicago United States 2010-05-25T19:15:47Z 2008-07-07T19:39:09Z 1 f83dd15abfb8b9b2c3017d1d6dd0bc64a6de23a9 Education & Research scientific workflow, service oriented architecture, grid computing, Petri net Lymphoma type prediction based on microarray data <p><span style="color: rgb(255, 0, 0);"><span style="font-size: large;">Scientific value</span></span></p> <ul> <li><span style="font-size: medium;">Using gene-expression patterns associated with DLBCL and FL to predict the lymphoma type of an unknown sample.</span></li> <li><span style="font-size: medium;">Using SVM (Support Vector Machine) to classify data, and predicting the tumor types of unknown examples.</span></li> </ul> <p><span style="color: rgb(255, 0, 0);"><span style="font-size: large;">Steps</span></span></p> <ul> <li><span style="font-size: medium;">Querying training data from experiments stored in caArray.<br /> </span></li> <li><span style="font-size: medium;">Preprocessing, or normalize the microarray data.<br /> </span></li> <li><span style="font-size: medium;">Adding training and testing data into SVM service to get classification result. </span></li> </ul> 1 0 2009-04-23T17:10:37Z 2009-04-23T17:15:00Z lymphoma_type_prediction_based_on_microarray_data_846970.t2flow