An ontology design methodology for Knowledge-Based systems with application to bioinformatics

Research areas:

• Uncategorized

Year:

2012

Type of Publication:

In Proceedings

Keywords:

bioinformatics, biological techniques, knowledge based systems

Authors:

• Antonino Fiannaca
• Massimo LaRosa
• Riccardo Rizzo
• Alfonso Urso
• Salvatore Gaglio

Book title:

Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2012 IEEE Symposium on

Pages:

85 - 91

Month:

May

ISBN:

978-1-4673-1190-8

Abstract:

Ontologies are formal knowledge representation models. Knowledge organization is a fundamental requirement in order to develop Knowledge-Based systems. In this paper we present Data-Problem-Solver (DPS) approach, a new ontological paradigm that allows the knowledge designer to model and represent a Knowledge Base (KB) for expert systems. Our approach clearly distinguishes among the knowledge about a problem to resolve (answering the “what to do” question), the solver method to resolve it (answering the “how to do” question) and the type of input data required (answering the “what I need” question). The main purpose of the proposed paradigm is to facilitate the generalization of the application domain and the modularity and the expandability of the represented knowledge. The proposed DPS ontological approach is applied to the modelling of the knowledge about a bioinformatics application scenario: the protein complex extraction from a protein-protein interaction network.