This paper proposes a novel method for text mining on the Grid, aimed at pointing out hidden relationships for hypothesis generation and suitable for semi-interactive querying. The method is based on unsupervised clustering and the outputs are visualized with contextual information. Grid implementation is crucial for feasibility. We demonstrate it with a mining run for discovering genes-diseases associations from bibliographic sources and annotated databases. The proposed methodology is in view of a Grid architecture specialized in bioinformatics mining tasks. Some performance considerations are provided. © 2009 IEEE.
|Titolo:||Discovering genes-diseaes associations from specialized bibliography using the grid|
|Autori interni:||GIORDANO, Daniela|
|Data di pubblicazione:||2009|
|Rivista:||IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE|
|Appare nelle tipologie:||1.1 Articolo in rivista|