title: Text Mining approaches for automated literature knowledge extraction and representation.
abstract: Due to the overwhelming volume of published scientific papers, information tools for automated literature analysis are essential to support current biomedical research. We have developed a knowledge extraction tool to help researcher in discovering useful information which can support their reasoning process. The tool is composed of a search engine based on Text Mining and Natural Language Processing techniques, and an analysis module which process the search results in order to build annotation similarity networks. We tested our approach on the available knowledge about the genetic mechanism of cardiac diseases, where the target is to find both known and possible hypothetical relations between specific candidate genes and the trait of interest. We show that the system i) is able to effectively retrieve medical concepts and genes and ii) plays a relevant role assisting researchers in the formulation and evaluation of novel literature-based hypotheses.
authors.affiliation: Center for Tissue Engineering University of Pavia, Italy. angelo.nuzzo@unipv.it
authors.forename: Angelo
authors.initials: A
authors.lastname: Nuzzo
authors.forename: Francesca
authors.initials: F
authors.lastname: Mulas
authors.forename: Matteo
authors.initials: M
authors.lastname: Gabetta
authors.forename: Eloisa
authors.initials: E
authors.lastname: Arbustini
authors.forename: Blaz
authors.initials: B
authors.lastname: Zupan
authors.forename: Cristiana
authors.initials: C
authors.lastname: Larizza
authors.forename: Riccardo
authors.initials: R
authors.lastname: Bellazzi
mesh_terms: D000043:Abstracting and Indexing / Q000379:methods; D057225:Data Mining / Q000379:methods*; D016206:Databases, Bibliographic; D006331:Heart Diseases / Q000235:genetics; D009323:Natural Language Processing