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.
|Titolo della pubblicazione ospite||Computational Intelligence Methods for Bioinformatics and Biostatistics: 6th international meeting CIBB 2009|
|Numero di pagine||15|
|Stato di pubblicazione||Published - 2010|
|Nome||LECTURE NOTES IN COMPUTER SCIENCE|
- Theoretical Computer Science