Cover Image

Classification of Protein Sequences using the Growing Self-Organizing Map

Protein sequence analysis is an important task in bioinformatics. The classification of protein sequences into groups is beneficial for further analysis of the structures and roles of a particular group of protein in biological process. It also allows an unknown or newly found sequence to be identif...

Full description

Saved in:
Bibliographic Details
Main Author: Ahmad, N.
Format: Conference or Workshop Item
Language:English
Published: 2008
Subjects:
Q Science (General)
Online Access:http://eprints.utem.edu.my/id/eprint/90/1/Norashikin__iciafs2008.pdf
http://eprints.utem.edu.my/id/eprint/90/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utem.eprints.90
record_format eprints
spelling my.utem.eprints.902015-05-28T02:16:42Z http://eprints.utem.edu.my/id/eprint/90/ Classification of Protein Sequences using the Growing Self-Organizing Map Ahmad, N. Q Science (General) Protein sequence analysis is an important task in bioinformatics. The classification of protein sequences into groups is beneficial for further analysis of the structures and roles of a particular group of protein in biological process. It also allows an unknown or newly found sequence to be identified by comparing it with protein groups that have already been studied. In this paper, we present the use of growing self-organizing map (GSOM), an extended version of the self-organizing map (SOM) in classifying protein sequences. With its dynamic structure, GSOM facilitates the discovery of knowledge in a more natural way. This study focuses on two aspects; analysis of the effect of spread factor parameter in the GSOM to the node growth and the identification of grouping and subgrouping under different level of abstractions by using the spread factor. 2008-12 Conference or Workshop Item NonPeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/90/1/Norashikin__iciafs2008.pdf Ahmad, N. (2008) Classification of Protein Sequences using the Growing Self-Organizing Map. In: 4th International Conference on Information and Automation for Sustainability, 2008. ICIAFS 2008. .
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic Q Science (General)
spellingShingle Q Science (General)
Ahmad, N.
Classification of Protein Sequences using the Growing Self-Organizing Map
description Protein sequence analysis is an important task in bioinformatics. The classification of protein sequences into groups is beneficial for further analysis of the structures and roles of a particular group of protein in biological process. It also allows an unknown or newly found sequence to be identified by comparing it with protein groups that have already been studied. In this paper, we present the use of growing self-organizing map (GSOM), an extended version of the self-organizing map (SOM) in classifying protein sequences. With its dynamic structure, GSOM facilitates the discovery of knowledge in a more natural way. This study focuses on two aspects; analysis of the effect of spread factor parameter in the GSOM to the node growth and the identification of grouping and subgrouping under different level of abstractions by using the spread factor.
format Conference or Workshop Item
author Ahmad, N.
author_facet Ahmad, N.
author_sort Ahmad, N.
title Classification of Protein Sequences using the Growing Self-Organizing Map
title_short Classification of Protein Sequences using the Growing Self-Organizing Map
title_full Classification of Protein Sequences using the Growing Self-Organizing Map
title_fullStr Classification of Protein Sequences using the Growing Self-Organizing Map
title_full_unstemmed Classification of Protein Sequences using the Growing Self-Organizing Map
title_sort classification of protein sequences using the growing self-organizing map
publishDate 2008
url http://eprints.utem.edu.my/id/eprint/90/1/Norashikin__iciafs2008.pdf
http://eprints.utem.edu.my/id/eprint/90/
_version_ 1665905239061954560
score 13.211869

Similar Items