miRiaD: A Text Mining Tool for Detecting Associations of microRNAs with Diseases.

Journal: Journal of biomedical semantics
Published Date: Apr 29, 2016

Abstract

BACKGROUND: MicroRNAs are increasingly being appreciated as critical players in human diseases, and questions concerning the role of microRNAs arise in many areas of biomedical research. There are several manually curated databases of microRNA-disease associations gathered from the biomedical literature; however, it is difficult for curators of these databases to keep up with the explosion of publications in the microRNA-disease field. Moreover, automated literature mining tools that assist manual curation of microRNA-disease associations currently capture only one microRNA property (expression) in the context of one disease (cancer). Thus, there is a clear need to develop more sophisticated automated literature mining tools that capture a variety of microRNA properties and relations in the context of multiple diseases to provide researchers with fast access to the most recent published information and to streamline and accelerate manual curation.

Authors

  • Samir Gupta
    Department of Computer and Information Sciences, University of Delaware, Newark, DE, 19711, USA. sgupta@udel.edu.
  • Karen E Ross
    Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE, 19711, USA.
  • Catalina O Tudor
    Department of Computer and Information Sciences, University of Delaware, Newark, DE, 19711, USA.
  • Cathy H Wu
  • Carl J Schmidt
    Department of Food and Animal Sciences, University of Delaware, Newark, DE, 19711, USA.
  • K Vijay-Shanker

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