Title page for ETD etd-04192004-011825


Type of Document Dissertation
Author Bing, Nan
URN etd-04192004-011825
Title Statistical Analysis of Gene Expression Profile: Transcription Network Inference and Sample Classification
Degree PhD
Department Genetics, Bioinformatics, and Computational Biology
Advisory Committee
Advisor Name Title
Hoeschele, Ina Committee Chair
Maroof, M. A. Saghai Committee Member
Mendes, Pedro J. P. Committee Member
Ramakrishnan, Naren Committee Member
ye, keying Committee Member
Keywords
  • Structural Equation Model
  • Classification
  • Mixture Model
  • Gene Network
  • Genetical Genomics
  • Microarray
Date of Defense 2004-04-05
Availability unrestricted
Abstract
The copious information generated from transcriptomes gives us an opportunity to learn biological processes as integrated systems; however, due to numerous sources of variation, high dimensions of data structure, various levels of data quality, and different formats of the inputs, dissecting and interpreting such data presents daunting challenges to scientists. The goal of this research is to provide improved and new statistical tools for analyzing transcriptomes data to identify gene expression patterns for classifying samples, to discover regulatory gene networks using natural genetic perturbations, to develop statistical methods for model fitting and comparison of biochemical networks, and eventually to advance our capability to understand the principles of biological processes at the system level.
Files
  Filename       Size       Approximate Download Time (Hours:Minutes:Seconds) 
 
 28.8 Modem   56K Modem   ISDN (64 Kb)   ISDN (128 Kb)   Higher-speed Access 
  Thesis.pdf 748.65 Kb 00:03:27 00:01:46 00:01:33 00:00:46 00:00:03

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