• English
  • Deutsch
  • Log In
    Password Login
    or
  • Research Outputs
  • Projects
  • Researchers
  • Institutes
  • Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. BELIEF - a semiautomatic workflow for BEL network creation
 
  • Details
  • Full
Options
2014
Conference Paper
Titel

BELIEF - a semiautomatic workflow for BEL network creation

Abstract
In order to build networks for systems biology from the literature an UIMA based extraction workflow using various named entity recognition processes and different relation extraction methods has been composed. The Unstructured Information Management architecture (UIMA) is a Java- based framework that allows assembling complicated workflows from a set of NLP components. The new system is processing scientific articles and is writing the open-access biological expression language (BEL) as output. BEL is a machine and human readable language with defined knowledge statements that can be used for knowledge representation, causal reasoning, and hypothesis generation. In order to curate the automatically derived BEL statements, our workflow integrates a curation interface that provides access to BEL statements generated by text mining and that integrates supporting information to facilitate manual curation. By using the semi-automated curation pipeline, expert time to model relevant causal relationships in BEL could be significantly reduced. In this paper the UIMA workflow and key features of the curation interface are described.
Author(s)
Fluck, Juliane
Madan, Sumit
Ansari, Sam
Szostak, Justyna
Hoeng, Julia
Zimmermann, Marc
Hofmann-Apitius, Martin
Peitsch, Manuel C
Hauptwerk
SMBM 2014, 6th International Symposium on Semantic Mining in Biomedicine. Proceedings. Online resource
Konferenz
International Symposium on Semantic Mining in Biomedicine (SMBM) 2014
Thumbnail Image
Externer Link
Externer Link
Language
English
google-scholar
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI
  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Send Feedback
© 2022