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Created: 11/05/10 @ 19:04:30 | Last updated: 11/05/10 @ 19:04:32
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License: Creative Commons Attribution-Share Alike 3.0 Unported License
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.
Rating: 5.0 / 5 (1 rating) | Versions: 7 | Reviews: 0 | Comments: 0 | Citations: 3 Viewed: 583 times | Downloaded: 227 times Tags (11): |
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Created: 23/04/09 @ 17:25:04 | Last updated: 03/09/11 @ 21:57:43
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License: Creative Commons Attribution-Share Alike 3.0 Unported License
Input CQL of the lymphoma prediction workflow at http://www.myexperiment.org/workflows/746?version=1. It is only for the purpose of illustration and NOT needed to run the workflow since the input has already been embedded.
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Created: 23/04/09 @ 17:37:16 | Last updated: 03/09/11 @ 21:56:29
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License: Creative Commons Attribution-Share Alike 3.0 Unported License
Output of the lymphoma prediction workflow at http://www.myexperiment.org/workflows/746?version=1. It shows the lymphoma type prediction results. It contains lymphoma type predictions for 38 samples and there is only one error (on testSample_4).
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Created: 23/04/09 @ 20:06:51
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License: Creative Commons Attribution-Share Alike 3.0 Unported License
testing on Ubuntu Linux 8.0.4 + Java 1.5_16
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