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Detecting essential genes in microarray dataset with unequal number of gene probes
Title
Detecting essential genes in microarray dataset with unequal number of gene probes.
Creator
Zhang, Wei, Qian, Lianfen, Charles E. Schmidt College of Science, Department of Mathematical Sciences
Abstract/Description
Microarray technology is a powerful approach for genomic research, which allows the monitoring of expressing profiles for tens of thousands genes in parallel and is already producing huge amounts of data. This thesis is motivated by a special microarray dataset for the bacteria Yersinia Pestis. It contains more than four thousands genes and each gene has different number of observations. The main purpose of this thesis is to detect essentially functional genes. Gene level adjusted multiple t...
Show moreMicroarray technology is a powerful approach for genomic research, which allows the monitoring of expressing profiles for tens of thousands genes in parallel and is already producing huge amounts of data. This thesis is motivated by a special microarray dataset for the bacteria Yersinia Pestis. It contains more than four thousands genes and each gene has different number of observations. The main purpose of this thesis is to detect essentially functional genes. Gene level adjusted multiple t‐test is proposed to handle the problem of unequal number of observations. Furthermore, a comparation study of our method with two other existing methods (Behrens‐Fisher method and Hotelling t‐square method) are presented. The comparison results show that our proposed methods is the best for identifying essential genes.
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Date Issued
2012
PURL
http://purl.flvc.org/fau/fd/FA00004261
Format
Document (PDF)
Detection of multiple change-points in hazard models
Title
Detection of multiple change-points in hazard models.
Creator
Zhang, Wei, Qian, Lianfen, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Mathematical Sciences
Abstract/Description
Change-point detection in hazard rate function is an important research topic in survival analysis. In this dissertation, we firstly review existing methods for single change-point detection in piecewise exponential hazard model. Then we consider the problem of estimating the change point in the presence of right censoring and long-term survivors while using Kaplan-Meier estimator for the susceptible proportion. The maximum likelihood estimators are shown to be consistent. Taking one step...
Show moreChange-point detection in hazard rate function is an important research topic in survival analysis. In this dissertation, we firstly review existing methods for single change-point detection in piecewise exponential hazard model. Then we consider the problem of estimating the change point in the presence of right censoring and long-term survivors while using Kaplan-Meier estimator for the susceptible proportion. The maximum likelihood estimators are shown to be consistent. Taking one step further, we propose an counting process based and least squares based change-point detection algorithm. For single change-point case, consistency results are obtained. We then consider the detection of multiple change-points in the presence of long-term survivors via maximum likelihood based and counting process based method. Last but not least, we use a weighted least squares based and counting process based method for detection of multiple change-points with long-term survivors and covariates. For multiple change-points detection, simulation studies show good performances of our estimators under various parameters settings for both methods. All methods are applied to real data analyses.
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Date Issued
2014
PURL
http://purl.flvc.org/fau/fd/FA00004173
Subject Headings
Problem solving--Data processing., Process control--Statistical methods., Point processes., Mathematical statistics., Failure time data analysis--Data processing., Survival analysis (Biometry)--Data processing.
Format
Document (PDF)
VLSI implementable thinning algorithm
Title
A VLSI implementable thinning algorithm.
Creator
Zhang, Wei, Florida Atlantic University, Shankar, Ravi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
Thinning is a very important step in a Character Recognition System. This thesis evolves a thinning algorithm that can be hardware implemented to improve the speed of the process. The software thinning algorithm features a simple set of rules that can be applied on both hexagonal and orthogonal character images. The hardware architecture features the SIMD structure, simple processing elements and near neighbor communications. The algorithm was simulated against the U.S. Postal Service...
Show moreThinning is a very important step in a Character Recognition System. This thesis evolves a thinning algorithm that can be hardware implemented to improve the speed of the process. The software thinning algorithm features a simple set of rules that can be applied on both hexagonal and orthogonal character images. The hardware architecture features the SIMD structure, simple processing elements and near neighbor communications. The algorithm was simulated against the U.S. Postal Service Character Database. The architecture, evolved with consideration of both the software constraints and the physical layout limitations, was simulated using VHDL hardware description language. Subsequent to VLSI design and simulations the chip was fabricated. The project provides for a feasibility study in utilizing the parallel processor architecture for the implementation of a parallel image thinning algorithm. It is hoped that such a hardware implementation will speed up the processing and lead eventually to a real time system.
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Date Issued
1992
PURL
http://purl.flvc.org/fcla/dt/14837
Subject Headings
Optical character recognition devices--Computer simulation, Algorithms, Integrated circuits--Very large scale integration
Format
Document (PDF)