PESCADOR, a web-based tool to assist text-mining of biointeractions extracted from PubMed queries
1 Computational Biology and Data Mining Group, Max Delbrück Center for Molecular Medicine. Robert-Rössle-Strasse. 10, D-13125, Berlin, Germany
2 Laboratório de Biodados, Dpto. de Bioquímica e Imunologia, ICB - UFMG. 31270-901, Belo Horizonte - MG, Brazil
3 São Paulo Branch, Ludwig Institute for Cancer Research, 01323-903, São Paulo - SP, Brazil
BMC Bioinformatics 2011, 12:435 doi:10.1186/1471-2105-12-435Published: 9 November 2011
Biological function is greatly dependent on the interactions of proteins with other proteins and genes. Abstracts from the biomedical literature stored in the NCBI's PubMed database can be used for the derivation of interactions between genes and proteins by identifying the co-occurrences of their terms. Often, the amount of interactions obtained through such an approach is large and may mix processes occurring in different contexts. Current tools do not allow studying these data with a focus on concepts of relevance to a user, for example, interactions related to a disease or to a biological mechanism such as protein aggregation.
To help the concept-oriented exploration of such data we developed PESCADOR, a web tool that extracts a network of interactions from a set of PubMed abstracts given by a user, and allows filtering the interaction network according to user-defined concepts. We illustrate its use in exploring protein aggregation in neurodegenerative disease and in the expansion of pathways associated to colon cancer.