Background: The rapidly increasing biological literature is a key resource to automatically extract and gain knowledge concerning biological elements and their relations. Knowledge Networks are helpful tools in the context of biological knowledge discovery and modeling. Results: We introduce a novel system called NETME, which, starting from a set of full-texts obtained from PubMed, through an easy-to-use web interface, interactively extracts biological elements from ontological databases and then synthesizes a network inferring relations among such elements. The results clearly show that our tool is capable of inferring comprehensive and reliable biological networks.

NETME: on-the-fly knowledge network construction from biomedical literature

Ferragina P.;
2022-01-01

Abstract

Background: The rapidly increasing biological literature is a key resource to automatically extract and gain knowledge concerning biological elements and their relations. Knowledge Networks are helpful tools in the context of biological knowledge discovery and modeling. Results: We introduce a novel system called NETME, which, starting from a set of full-texts obtained from PubMed, through an easy-to-use web interface, interactively extracts biological elements from ontological databases and then synthesizes a network inferring relations among such elements. The results clearly show that our tool is capable of inferring comprehensive and reliable biological networks.
2022
Muscolino, A.; Di Maria, A.; Rapicavoli, R. V.; Alaimo, S.; Bellomo, L.; Billeci, F.; Borzi, S.; Ferragina, P.; Ferro, A.; Pulvirenti, A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1123036
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