Collection-Wide Extraction of Protein-Protein Interactions

Evidence in support of relationships among biomedical entities, such as protein-protein interactions, can be gathered from a multiplicity of sources. The larger the pool of evidence, the more likely a given interaction can be considered to be. In the context of biomedical text mining, this elementary observation can be translated into an approach that seeks to find in the literature all available evidence for a given interaction, and thus provides a reliable means to assign it a likelihood score before delivering the results to an end user. In this paper we present the initial results of an on-going collaborative project between a major pharmaceutical company and an academic group with extensive expertise in biomedical text mining, with the goal of extracting protein-protein interactions from a large pool of supporting papers. Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-101472 Published Version Originally published at: Furrer, Lenz; Clematide, Simon; Marques, Hernani; Rodriguez‐Esteban, Raul; Romacker, Martin; Rinaldi, Fabio (2014). Collection‐Wide Extraction of Protein‐Protein Interactions. In: 6th International Symposium on Semantic Mining in Biomedicine, Aveiro, Portugal, 6 October 2014 7 October 2014, 61-66. Collection-Wide Extraction of Protein-Protein Interactions