Regulatory signal detection in genomic sequences

This thesis is to develop a general and robust approach for the detection of different types of regulatory signals in eukaryotic genomic DNA sequences. We proposed to use lower-order Markov models for encoding the input sequences for the prediction of signals by neural networks and demonstrated the...

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Main Author: Ho, Sy Loi.
Other Authors: Rajapakse, Jagath Chandana
Format: Theses and Dissertations
Published: 2008
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Online Access:http://hdl.handle.net/10356/2656
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-26562023-03-04T00:30:04Z Regulatory signal detection in genomic sequences Ho, Sy Loi. Rajapakse, Jagath Chandana School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences This thesis is to develop a general and robust approach for the detection of different types of regulatory signals in eukaryotic genomic DNA sequences. We proposed to use lower-order Markov models for encoding the input sequences for the prediction of signals by neural networks and demonstrated the efficacy of the Markov/neural approach in the detection of three signals, namely, splice sites, translation initiation sites, and transcription start sites. The low-order Markov models incorporate useful biological knowledge such as the differences in nucleotide distributions observed in different functional regions adjoining the signals and the homology of potential sites. The neural networks, being large non-parametric non-linear models, combine the outputs from Markov chains to derive long-range and complex interactions among nucleotides, which are related to the actual identification of signals. The novel Markov/neural hybrid mode was shown capable of approximating higher-order Markov models of signals, and provides an efficient and feasible method of learning model parameters, leading to the better detection of signals. Doctor of Philosophy (SAS) 2008-09-17T09:07:11Z 2008-09-17T09:07:11Z 2005 2005 Thesis Ho, S. L. (2005). Regulatory signal detection in genomic sequences. Doctoral thesis, Nanyang Technological University, Singapore. http://hdl.handle.net/10356/2656 Nanyang Technological University application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
topic DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences
spellingShingle DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences
Ho, Sy Loi.
Regulatory signal detection in genomic sequences
description This thesis is to develop a general and robust approach for the detection of different types of regulatory signals in eukaryotic genomic DNA sequences. We proposed to use lower-order Markov models for encoding the input sequences for the prediction of signals by neural networks and demonstrated the efficacy of the Markov/neural approach in the detection of three signals, namely, splice sites, translation initiation sites, and transcription start sites. The low-order Markov models incorporate useful biological knowledge such as the differences in nucleotide distributions observed in different functional regions adjoining the signals and the homology of potential sites. The neural networks, being large non-parametric non-linear models, combine the outputs from Markov chains to derive long-range and complex interactions among nucleotides, which are related to the actual identification of signals. The novel Markov/neural hybrid mode was shown capable of approximating higher-order Markov models of signals, and provides an efficient and feasible method of learning model parameters, leading to the better detection of signals.
author2 Rajapakse, Jagath Chandana
author_facet Rajapakse, Jagath Chandana
Ho, Sy Loi.
format Theses and Dissertations
author Ho, Sy Loi.
author_sort Ho, Sy Loi.
title Regulatory signal detection in genomic sequences
title_short Regulatory signal detection in genomic sequences
title_full Regulatory signal detection in genomic sequences
title_fullStr Regulatory signal detection in genomic sequences
title_full_unstemmed Regulatory signal detection in genomic sequences
title_sort regulatory signal detection in genomic sequences
publishDate 2008
url http://hdl.handle.net/10356/2656
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