A Proposed Knowledge Based Approach for Solving Proteomics Issues

Daniele Peri, Salvatore Gaglio, Massimo La Rosa, Antonino Fiannaca, Daniele Peri, Alfonso Urso, Salavatore Gaglio, Riccardo Rizzo, Antonino Fiannaca, Massimo La Rosa

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Abstract

In this paper we present a novel knowledge-based approach that aims at helping scientists to face and resolve a large number of proteomics problem. The system architecture is based on an ontologyto model the knowledge base, a reasoner that starting from the user’s request and a set of rules builds the workflow of tasks to be done, and an executor that runs the algorithms and software scheduled by the reasoner. The system can interact with the user showing him intermediate results and several options in order to refine the workflow and supporting him to choose among different forks. Thanks to the presence of the knowledge base and the modularity provided by the ontology, the system canbe enriched with new expertise in order to deal with other proteomic or bioinformatics issues. Two possible application scenarios are presented.
Lingua originaleEnglish
Titolo della pubblicazione ospiteComputational Intelligence Methods for Bioinformatics and Biostatistics: 6th international meeting CIBB 2009
Pagine304-318
Numero di pagine15
Stato di pubblicazionePublished - 2010

Serie di pubblicazioni

NomeLECTURE NOTES IN COMPUTER SCIENCE

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
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