Date of Award
Summer 2007
Document Type
Thesis - Restricted
Degree Name
Master of Science (MS)
Department
Electrical and Computer Engineering
First Advisor
Feng, Xin
Second Advisor
Povinelli, Richard J.
Third Advisor
Struble, Craig A.
Abstract
A novel method for temporal profiling of short time series microarray data, inspired by reconstructed phase space (RPS) theory and the minimum entropy clustering algorithm is introduced. The augmented first difference space provides addition information, relating to the trend of the time series, for the clustering algorithm. This resultant higher dimension space is clustered using the minimum entropy clustering algorithm. The means of the subsequent clusters are then translated into a trend matrix, and a k-means clustering algorithm is applied to group the trends together. The results showed the proposed method was able to group genes with similar trends together and comparing with current approaches this new approach is able to find tighter clusters within the data.
Recommended Citation
Szeto, Peter Wei De, "A Temporal Difference Representation for Temporal Profiling of Short Time Series Microarray Gene Expression Data" (2007). Master's Theses (1922-2009) Access restricted to Marquette Campus. 4197.
https://epublications.marquette.edu/theses/4197