Sample A: Cover Page of Thesis, Project, or Dissertation Proposal

Summary
and normal samples, as cleansed by the methodology presented in Chapter 2.
K-means clustering was used to calculate the information gain of the cleansed
ProbeSets. The gain criterion demonstrates an efficient methodology to
down select to a manageable candidate gene list. This candidate gene lists
demonstrates accurate prediction rates for the three disease groups, for kNN
and LDA classification algorithms. More importantly what is known about
the biology of these genes suggests intriguing differences in cell cycle control
mechanisms in the different groups. In particular, the findings suggest the
occurrence of aberrant cytokinesis, which may underlie or be resultant in
DNA damage elucidating the p53 dependent pathway in the squamous cell
carcinoma samples.
Microarray experiments assess the concentration of a samples’ transcript levels at a given point in
time. These measurements are the result of a semi-quantitative interpretation of the amount of
fluorescence at a given probe spot. The probes at these spots are present in sufficient
concentration to drive the expected duplex product formation, but the variation in the response
cannot be assessed since most commercial platforms do not provide spot replicates. The
measurements of fluorescent intensity are interpreted to represent the concentrations of specific
regions of a transcript and for those platforms like Affymetrix that provide multiple
measurements over a transcript this redundancy is meant to be equivalent to the spot replicate
feature. These platforms have sacrificed measurement replication, ignored scanner limitations,
have problematic background correction design and pay inadequate attention to known factors
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