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.
Parameters used in our filter: