Publication: DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes

DisGeNET is a comprehensive discovery platform designed to address a variety of questions concerning the genetic underpinning of human diseases. DisGeNET contains over 380 000 associations between >16 000 genes and 13 000 diseases, which makes it one of the largest repositories currently available of its kind. DisGeNET integrates expert-curated databases with text-mined data, covers information on Read more about Publication: DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes[…]

Publication: Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research

Background Current biomedical research needs to leverage and exploit the large amount of information reported in scientific publications. Automated text mining approaches, in particular those aimed at finding relationships between entities, are key for identification of actionable knowledge from free text repositories. We present the BeFree system aimed at identifying relationships between biomedical entities with Read more about Publication: Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research[…]

Conference: 6th International Symposium on Semantic Mining in Biomedicine

6th International Symposium on Semantic Mining in Biomedicine (SMBM), Aveiro, Portugal Laura I. Furlong, Alex Bravo, Janet Piñero, Núria Queralt-Rosinach and Michael Rautschka (Parc de Salut Mar Barcelona) presented BeFree: a text mining system to extract relations between genes, diseases and drugs for translational researc

Publication: A Knowledge-Driven Approach to Extract Disease-Related Biomarkers from the Literature

The biomedical literature represents a rich source of biomarker information. However, both the size of literature databases and their lack of standardization hamper the automatic exploitation of the information contained in these resources. Text mining approaches have proven to be useful for the exploitation of information contained in the scientific publications. Here, we show that Read more about Publication: A Knowledge-Driven Approach to Extract Disease-Related Biomarkers from the Literature[…]