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Document Type : Latin Dissertation
Language of Document : English
Record Number : 151602
Doc. No : ET23394
Main Entry : QICHENG MA
Title Proper : KNOWLEDGE DISCODRY IN BIOLOGICAL DATABASES: A NEWRAL NETWORK APPROACH
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : Knowledge discovery in databases, also known as data mining, is aimed to findsignificant information from a set of data. The knowledge to be mined from thedataset may refer to patterns, association rules, classification and clustering rules,and so forth. In this dissertation, we present a neural network approach to findingknowledge in biological databases. Specifically, we propose new methods to processbiological sequences in two case studies: the classification of protein sequences andthe prediction of E. Coli promoters in DNA sequences. Our proposed methods, basedon neural network architectures, combine techniques ranging from Bayesian inference,coding theory, feature selection, dimensionality reduction, to dynamic programmingand machine learning algorithms. Empirical studies show that the proposed methodsoutperform previously published methods and have excellent performance on thelatest dataset. We have implemented the proposed algorithms into an infrastructure,called Genome Mining,.....-....,....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL46633.pdf
Title and statement of responsibility and : KNOWLEDGE DISCODRY IN BIOLOGICAL DATABASES: A NEWRAL NETWORK APPROACH [Thesis]
 
 
 
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