Source:

 

@ARTICLE{West2001,

author = {M. West and C. Blanchette and H. Dressman and E. Huang and S. Ishida and R. Spang and H. Zuzan and J. A. Olson and J. R. Marks and J. R. Nevins},

title = {Predicting the clinical status of human breast cancer by using gene expression profiles.},

journal = {Proc Natl Acad Sci U S A},

year = {2001},

volume = {98},

pages = {11462--11467},

number = {20},

month = {Sep},

doi = {10.1073/pnas.201162998},

url = {http://dx.doi.org/10.1073/pnas.201162998}

}

 

Original data: http://data.cgt.duke.edu/west.php

 

Description:

 

The authors have developed Bayesian regression models that provide predictive capability based on gene expression data derived from DNA microarray analysis of a series of primary breast cancer samples. These patterns have the capacity to discriminate breast tumors on the basis of estrogen receptor status and also on the categorized lymph node status. Their data consisted of estrogen-receptor-positive (ER+) and estrogen-receptor-negative (ER-) tumors.

 

 

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