Empirical robustness evaluation of DNA-based clustering methods

DNA-based computation is one of the latest computation paradigms. Compared to conventional methods that obtain their end results via electronic processes, aDNA-based approach obtains its result from bio-chemical reactions. It is essential in this approach for all experimental processes to be perform...

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Main Authors:	Rohani, Abu Bakar, Watada, Junzo
Format:	Article
Language:	English
Published:	Taylor & Francis 2011
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/25578/ http://umpir.ump.edu.my/id/eprint/25578/ http://umpir.ump.edu.my/id/eprint/25578/ http://umpir.ump.edu.my/id/eprint/25578/1/Empirical%20robustness%20evaluation%20of%20DNA-based%20clustering%20methods.pdf

id	ump-25578
recordtype	eprints
spelling	ump-255782020-02-11T06:58:42Z http://umpir.ump.edu.my/id/eprint/25578/ Empirical robustness evaluation of DNA-based clustering methods Rohani, Abu Bakar Watada, Junzo QA76 Computer software DNA-based computation is one of the latest computation paradigms. Compared to conventional methods that obtain their end results via electronic processes, aDNA-based approach obtains its result from bio-chemical reactions. It is essential in this approach for all experimental processes to be performed without fault. However, some errors may occur while carrying out these bio-chemical experiments. Consequently, it is necessary to overcome their weaknesses. The aim of this study is to examine the robustness of DNA-based techniques in solving a clustering problem. In the broadest sense, robustness can be defined as being able to withstand stresses, pressures, or changes in procedure or circumstance. To examine the robustness of the approach, this research examined the impact of error or added noise on DNA-based procedure results. Comparative studies of different error sets are also provided here. Additionally, two well-known conventional clustering algorithms (Fuzzy C-means and k-means) were applied to the same error sets, to study the reliability and validity of results when comparing DNA-based clustering. Taylor & Francis 2011 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25578/1/Empirical%20robustness%20evaluation%20of%20DNA-based%20clustering%20methods.pdf Rohani, Abu Bakar and Watada, Junzo (2011) Empirical robustness evaluation of DNA-based clustering methods. International Journal of Intelligent Computing in Medical Sciences and Image Processing, 4 (1). pp. 1-12. ISSN 1931-308X https://doi.org/10.1080/1931308X.2011.10644179 https://doi.org/10.1080/1931308X.2011.10644179
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Rohani, Abu Bakar Watada, Junzo Empirical robustness evaluation of DNA-based clustering methods
description	DNA-based computation is one of the latest computation paradigms. Compared to conventional methods that obtain their end results via electronic processes, aDNA-based approach obtains its result from bio-chemical reactions. It is essential in this approach for all experimental processes to be performed without fault. However, some errors may occur while carrying out these bio-chemical experiments. Consequently, it is necessary to overcome their weaknesses. The aim of this study is to examine the robustness of DNA-based techniques in solving a clustering problem. In the broadest sense, robustness can be defined as being able to withstand stresses, pressures, or changes in procedure or circumstance. To examine the robustness of the approach, this research examined the impact of error or added noise on DNA-based procedure results. Comparative studies of different error sets are also provided here. Additionally, two well-known conventional clustering algorithms (Fuzzy C-means and k-means) were applied to the same error sets, to study the reliability and validity of results when comparing DNA-based clustering.
format	Article
author	Rohani, Abu Bakar Watada, Junzo
author_facet	Rohani, Abu Bakar Watada, Junzo
author_sort	Rohani, Abu Bakar
title	Empirical robustness evaluation of DNA-based clustering methods
title_short	Empirical robustness evaluation of DNA-based clustering methods
title_full	Empirical robustness evaluation of DNA-based clustering methods
title_fullStr	Empirical robustness evaluation of DNA-based clustering methods
title_full_unstemmed	Empirical robustness evaluation of DNA-based clustering methods
title_sort	empirical robustness evaluation of dna-based clustering methods
publisher	Taylor & Francis
publishDate	2011
url	http://umpir.ump.edu.my/id/eprint/25578/ http://umpir.ump.edu.my/id/eprint/25578/ http://umpir.ump.edu.my/id/eprint/25578/ http://umpir.ump.edu.my/id/eprint/25578/1/Empirical%20robustness%20evaluation%20of%20DNA-based%20clustering%20methods.pdf
first_indexed	2023-09-18T22:39:21Z
last_indexed	2023-09-18T22:39:21Z
_version_	1777416810254041088

Empirical robustness evaluation of DNA-based clustering methods

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