et al's paper. It concerns one hundred thirty-three patients with stage I–III breast cancer. Patients were treated with chemotherapy prior to surgery. Patient response to the treatment can be classified as either a pathologic complete response (pCR) or residual disease (not-pCR). Hess et al developed and tested a reliable multigene predictor for treatment response on this data set, composed by a set of 26 genes having a high predictive value.
a list of two objects: dataframe with 133 observations of 26 features and factors indicating whether each sample (out of 133) is of type "not" or type "pcr"
The dataset splits into 2 parts (pCR and not pCR), on which network inference algorithms should be applied independently or in the multitask framework: only individuals from the same classes should be consider as independent and identically distributed.
J.A. Mejia, D. Booser, R.L. Theriault, U. Buzdar, P.J. Dempsey, R. Rouzier, N. Sneige, J.S. Ross, T. Vidaurre, H.L. Gomez, G.N. Hortobagyi, and L. Pustzai (2006). Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with Paclitaxel and Fluorouracil, Doxorubicin, and Cyclophosphamide in breast cancer, Journal of Clinical Oncology, vol. 24(26), pp. 4236–4244.
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