Min Mo

Graduation Semester and Year

2008

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Mathematics

Department

Mathematics

First Advisor

Doyle Hawkins

Abstract

This paper estimates the Langmuir parameters for probe on microarray then improves estimation of absolute transcript concentration using Langmuir adsorption model. We use the spike-in probes found on commercial microarrays, along with Langmuir adsorption model to estimate Langmuir parameters for spike-in probes, then combine with an assumed log-linear model for those Langmuir parameters in terms of the spike-in probe sequence features, to estimate the assumed-invariant model coefficients. These estimated coefficients are then used, along with the probe sequence features of the target probes, to estimate the Langmuir parameters for each target probe. Finally, these estimated Langmuir parameters are combined with the expression measurements to produce estimates of the absolute transcript concentrations. The performance of this method, which amounts to extrapolation of a model fit over the space of the spike-in probe features to the space of the target probe features, will depend on the extent of this extrapolation. Simulation results will be presented to describe the performance of the method. The optimal choice of spike-in probes is given to the chip design.

Disciplines

Mathematics | Physical Sciences and Mathematics

Comments

Degree granted by The University of Texas at Arlington

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