Making Gene Sets More Coherent
Full Text: Mahdavifard_Fariba_Fall2009.pdf
One important goal in microarray data analysis is to learn a predictor using a patient's microarray data to predict some important characteristics of that patient. The high dimensionality of data makes learning such classifiers very challenging. We tried to use prior biological knowledge to tackle the challenges. Our colleagues have produced clusters of genes with a common function, called "PBTs", for mouse and human. We hoped we could use each cluster as a single feature. This is most effective if each PBT is "coherent. They expect all PBTs to be coherent; but while mouse PBTs are coherent, human PBTs are not. In this thesis we propose a method, called MkCoh, to improve the coherency of each PBT by removing and flipping some genes. We expected the predictors based on the revised PBTs to be more accurate than the ones based on either the original PBTs, or on the original gene expression values. However, our experimental results did not demonstrate this; we explored some possible reasons.
Citation
F. Mahdavifard. "Making Gene Sets More Coherent". MSc Thesis, October 2009.| Keywords: | |
| Category: | MSc Thesis |
BibTeX
@mastersthesis{Mahdavifard:09,
author = {Fariba Mahdavifard},
title = {Making Gene Sets More Coherent},
year = 2009,
}Last Updated: September 03, 2013Submitted by Russ Greiner
