Name
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 ontology to 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 can be enriched with new expertise in order to deal with other proteomic or bioinformatics issues. Two possible application scenarios are presented. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-14571-1_23 | CIBB |
Keywords | Field | DocType |
bioinformatics issue,proteomics problem,possible application scenario,novel knowledge-based approach,knowledge base,large number,system architecture,different fork,new expertise,intermediate result,proteomics issue,proposed knowledge | Ontology,Executor,Semantic reasoner,Computer science,Expert system,Knowledge-based systems,Artificial intelligence,Knowledge base,Bioinformatics,Systems architecture,Workflow,Machine learning | Conference |
Volume | ISSN | ISBN |
6160 | 0302-9743 | 3-642-14570-1 |
Citations | PageRank | References |
0 | 0.34 | 17 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonino Fiannaca | 1 | 117 | 15.80 |
| Salavatore Gaglio | 2 | 0 | 0.34 |
| Massimo La Rosa | 3 | 114 | 14.59 |
| Daniele Peri | 4 | 24 | 10.14 |
| Riccardo Rizzo | 5 | 271 | 39.18 |
| Alfonso Urso | 6 | 138 | 19.99 |