A novel biological computation method for deriving and resolving discernibility relations

Ikno Kim; Junzo Watada; Jui Yu Wu; Yu Yi Chu

doi:10.1109/BIBE.2009.31

A novel biological computation method for deriving and resolving discernibility relations

Ikno Kim, Junzo Watada, Jui Yu Wu, Yu Yi Chu

Department of Biochemistry and Molecular Cell Biology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Corporate and advanced information and database technologies make it possible to solve potential and hidden problems, such as uncertainty data interactions, disputable resolutions, unclear processes, etc. In this case, a rough set method can be used to grasp characteristics of the classified objects included in those problems. The rough set method is often used for classifying data while figuring out the distinctive features of the given objects in problem solutions. These given object problems that emerge, especially in database handling and resolving discernibility relations with the rough set method, are often computed by electronic computations. On the other hand, in this paper, we basically focus on taking advantage of biological molecular functions to create a novel biological computation method with which we proposed to derive and resolve all the discernibility relations.

Original language	English
Title of host publication	Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009
Pages	9-14
Number of pages	6
DOIs	https://doi.org/10.1109/BIBE.2009.31
Publication status	Published - 2009
Event	2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009 - Taichung, Taiwan Duration: Jun 22 2009 → Jun 24 2009

Other

Other	2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009
Country/Territory	Taiwan
City	Taichung
Period	6/22/09 → 6/24/09

Keywords

Biological computation
Decision matrix
Decision table
Discernibility relation

ASJC Scopus subject areas

Information Systems
Biomedical Engineering
Health Informatics

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10.1109/BIBE.2009.31

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Kim, I, Watada, J, Wu, JY & Chu, YY 2009, A novel biological computation method for deriving and resolving discernibility relations. in Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009., 5211339, pp. 9-14, 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009, Taichung, Taiwan, 6/22/09. https://doi.org/10.1109/BIBE.2009.31

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abstract = "Corporate and advanced information and database technologies make it possible to solve potential and hidden problems, such as uncertainty data interactions, disputable resolutions, unclear processes, etc. In this case, a rough set method can be used to grasp characteristics of the classified objects included in those problems. The rough set method is often used for classifying data while figuring out the distinctive features of the given objects in problem solutions. These given object problems that emerge, especially in database handling and resolving discernibility relations with the rough set method, are often computed by electronic computations. On the other hand, in this paper, we basically focus on taking advantage of biological molecular functions to create a novel biological computation method with which we proposed to derive and resolve all the discernibility relations.",

keywords = "Biological computation, Decision matrix, Decision table, Discernibility relation",

author = "Ikno Kim and Junzo Watada and Wu, {Jui Yu} and Chu, {Yu Yi}",

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doi = "10.1109/BIBE.2009.31",

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booktitle = "Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009",

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AU - Kim, Ikno

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N2 - Corporate and advanced information and database technologies make it possible to solve potential and hidden problems, such as uncertainty data interactions, disputable resolutions, unclear processes, etc. In this case, a rough set method can be used to grasp characteristics of the classified objects included in those problems. The rough set method is often used for classifying data while figuring out the distinctive features of the given objects in problem solutions. These given object problems that emerge, especially in database handling and resolving discernibility relations with the rough set method, are often computed by electronic computations. On the other hand, in this paper, we basically focus on taking advantage of biological molecular functions to create a novel biological computation method with which we proposed to derive and resolve all the discernibility relations.

AB - Corporate and advanced information and database technologies make it possible to solve potential and hidden problems, such as uncertainty data interactions, disputable resolutions, unclear processes, etc. In this case, a rough set method can be used to grasp characteristics of the classified objects included in those problems. The rough set method is often used for classifying data while figuring out the distinctive features of the given objects in problem solutions. These given object problems that emerge, especially in database handling and resolving discernibility relations with the rough set method, are often computed by electronic computations. On the other hand, in this paper, we basically focus on taking advantage of biological molecular functions to create a novel biological computation method with which we proposed to derive and resolve all the discernibility relations.

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KW - Decision matrix

KW - Decision table

KW - Discernibility relation

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BT - Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009

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A novel biological computation method for deriving and resolving discernibility relations

Abstract

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Keywords

ASJC Scopus subject areas

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