Question-driven topic-based extraction of Protein-Protein Interaction Methods from biomedical literature

John Atkinson, Gerardo Montecinos, Dorothy Curtis

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


This paper proposes a novel topic-based model for identifying experimental mentions of Protein-Protein Interaction Method (PPIM) in the biomedical literature. The model combines topic-based classification models and some basic question-answering extraction techniques aiming at effectively detecting and identifying PPIM mentions on Protein-Protein Interactions. Unlike other state-of-the-art approaches, the approach captures underlying relationships within both input and output concept spaces by assuming the extraction task to be strongly driven by context provided by experts, usually in the form of a question to guide the search. Results indicate our topic-based question-driven approach obtained better results than other unsupervised learning probabilistic latent space models for detecting correct answers (PPIM mentions).

Original languageEnglish
Pages (from-to)170-180
Number of pages11
JournalInformation Sciences
StatePublished - 10 Sep 2016
Externally publishedYes


  • Biomedical text mining
  • Information access
  • Natural-language processing
  • Topic models


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