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Updated: Jun 25, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
Published on: October 13, 2023
Discovering genes-diseases associations from specialized literature using the grid
Alberto Faro1, Daniela Giordano, Francesco Maiorana
1Dipartimento di Ingegneria Informatica e Telecomunicazioni, Università di Catania, 95125 Catania, Italy. afaro@diit.unict.it
Abstract:
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.
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