Motivation: Our goal is to construct a model for genetic regulatory networks such that the
model class: (i) incorporates rule-based dependencies between genes; (ii) allows the …

Gene expression can be quantitatively analyzed by hybridizing fluor-tagged mRNA to targets
on a cDNA microarray. Comparison of gene expression levels arising from cohybridized …

… Sinha, ER Dougherty, Vol. TT23 • Optical Communication Receiver Design, Stephen B.
Alexander, Vol. … TT17 • An Introduction to Nonlinear Image Processing, ER Dougherty, J …

Motivation: Microarray classification typically possesses two striking attributes: (1) classifier
design and error estimation are based on remarkably small samples and (2) cross-validation …

… [78] RP Loce and ER Dougherty, “Optimal morphological restoration: The morphological
filter mean-absolute-error theorem,” Vis. Commun. Image Representation, vol. …

Motivation: Given the joint feature-label distribution, increasing the number of features always
results in decreased classification error; however, this is not the case when a classifier is …

… Dougherty a c … More discussions on the synergetic effects among features and the
impact on feature selection can be found in a study by Dougherty and Brun [26]. … Dougherty …

Selection of significant genes via expression patterns is an important problem in microarray
experiments. Owing to small sample size and the large number of variables (genes), the …

Motivation: The receiver operator characteristic (ROC) curves are commonly used in
biomedical applications to judge the performance of a discriminant across varying decision …

Motivation: A major objective of gene regulatory network modeling, in addition to gaining a
deeper understanding of genetic regulation and control, is the development of computational …