Discovering Weighted Patterns in Intron Sequences Using Self-Adaptive Harmony Search and Back-Propagation Algorithms

A hybrid self-adaptive harmony search and back-propagation mining system was proposed to discover weighted patterns in human intron sequences. By testing the weights under a lazy nearest neighbor classifier, the numerical results revealed the significance of these weighted patterns. Comparing these...

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Main Authors: Yin-Fu Huang, Chia-Ming Wang, Sing-Wu Liou
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2013/249034
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author Yin-Fu Huang
Chia-Ming Wang
Sing-Wu Liou
author_facet Yin-Fu Huang
Chia-Ming Wang
Sing-Wu Liou
author_sort Yin-Fu Huang
collection DOAJ
description A hybrid self-adaptive harmony search and back-propagation mining system was proposed to discover weighted patterns in human intron sequences. By testing the weights under a lazy nearest neighbor classifier, the numerical results revealed the significance of these weighted patterns. Comparing these weighted patterns with the popular intron consensus model, it is clear that the discovered weighted patterns make originally the ambiguous 5SS and 3SS header patterns more specific and concrete.
format Article
id doaj-art-d54a22ed87a74997991829c190720081
institution OA Journals
issn 1537-744X
language English
publishDate 2013-01-01
publisher Wiley
record_format Article
series The Scientific World Journal
spelling doaj-art-d54a22ed87a74997991829c1907200812025-08-20T02:19:58ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/249034249034Discovering Weighted Patterns in Intron Sequences Using Self-Adaptive Harmony Search and Back-Propagation AlgorithmsYin-Fu Huang0Chia-Ming Wang1Sing-Wu Liou2Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliu, Yunlin 640, TaiwanGraduate School of Engineering Science and Technology, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliu, Yunlin 640, TaiwanSupercomputing Research Center, National Chen Kung University, 1 University Road, Tainan, 70101, TaiwanA hybrid self-adaptive harmony search and back-propagation mining system was proposed to discover weighted patterns in human intron sequences. By testing the weights under a lazy nearest neighbor classifier, the numerical results revealed the significance of these weighted patterns. Comparing these weighted patterns with the popular intron consensus model, it is clear that the discovered weighted patterns make originally the ambiguous 5SS and 3SS header patterns more specific and concrete.http://dx.doi.org/10.1155/2013/249034
spellingShingle Yin-Fu Huang
Chia-Ming Wang
Sing-Wu Liou
Discovering Weighted Patterns in Intron Sequences Using Self-Adaptive Harmony Search and Back-Propagation Algorithms
The Scientific World Journal
title Discovering Weighted Patterns in Intron Sequences Using Self-Adaptive Harmony Search and Back-Propagation Algorithms
title_full Discovering Weighted Patterns in Intron Sequences Using Self-Adaptive Harmony Search and Back-Propagation Algorithms
title_fullStr Discovering Weighted Patterns in Intron Sequences Using Self-Adaptive Harmony Search and Back-Propagation Algorithms
title_full_unstemmed Discovering Weighted Patterns in Intron Sequences Using Self-Adaptive Harmony Search and Back-Propagation Algorithms
title_short Discovering Weighted Patterns in Intron Sequences Using Self-Adaptive Harmony Search and Back-Propagation Algorithms
title_sort discovering weighted patterns in intron sequences using self adaptive harmony search and back propagation algorithms
url http://dx.doi.org/10.1155/2013/249034
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AT chiamingwang discoveringweightedpatternsinintronsequencesusingselfadaptiveharmonysearchandbackpropagationalgorithms
AT singwuliou discoveringweightedpatternsinintronsequencesusingselfadaptiveharmonysearchandbackpropagationalgorithms