The huge amount of biological literature, which daily increases, represents a strategic resource to automatically extract and gain knowledge concerning relations among biological elements. Knowledge Networks are helpful tools in the context of biological knowledge discovery and modeling. Here we introduce a novel system called NETME, which, starting from a set of fulltext obtained from PubMed, through an easy-to-use web interface, interactively extracts a group of biological elements stored into a selected list of ontological databases and then synthesizes a network with inferred relations among such elements. The results clearly show that our tool is capable to efficiently and efficaciously infer reliable functional biological networks.
NETME: On-the-fly knowledge network construction from biomedical literature
P. Ferragina;
2020-01-01
Abstract
The huge amount of biological literature, which daily increases, represents a strategic resource to automatically extract and gain knowledge concerning relations among biological elements. Knowledge Networks are helpful tools in the context of biological knowledge discovery and modeling. Here we introduce a novel system called NETME, which, starting from a set of fulltext obtained from PubMed, through an easy-to-use web interface, interactively extracts a group of biological elements stored into a selected list of ontological databases and then synthesizes a network with inferred relations among such elements. The results clearly show that our tool is capable to efficiently and efficaciously infer reliable functional biological networks.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
