DES-ncRNA: A knowledgebase for exploring information about human micro and long noncoding RNAs based on literature-mining.

Journal: RNA biology
Published Date:

Abstract

Noncoding RNAs (ncRNAs), particularly microRNAs (miRNAs) and long ncRNAs (lncRNAs), are important players in diseases and emerge as novel drug targets. Thus, unraveling the relationships between ncRNAs and other biomedical entities in cells are critical for better understanding ncRNA roles that may eventually help develop their use in medicine. To support ncRNA research and facilitate retrieval of relevant information regarding miRNAs and lncRNAs from the plethora of published ncRNA-related research, we developed DES-ncRNA ( www.cbrc.kaust.edu.sa/des_ncrna ). DES-ncRNA is a knowledgebase containing text- and data-mined information from public scientific literature and other public resources. Exploration of mined information is enabled through terms and pairs of terms from 19 topic-specific dictionaries including, for example, antibiotics, toxins, drugs, enzymes, mutations, pathways, human genes and proteins, drug indications and side effects, mutations, diseases, etc. DES-ncRNA contains approximately 878,000 associations of terms from these dictionaries of which 36,222 (5,373) are with regards to miRNAs (lncRNAs). We provide several ways to explore information regarding ncRNAs to users including controlled generation of association networks as well as hypotheses generation. We show an example how DES-ncRNA can aid research on Alzheimer disease and suggest potential therapeutic role for Fasudil. DES-ncRNA is a powerful tool that can be used on its own or as a complement to the existing resources, to support research in human ncRNA. To our knowledge, this is the only knowledgebase dedicated to human miRNAs and lncRNAs derived primarily through literature-mining enabling exploration of a broad spectrum of associated biomedical entities, not paralleled by any other resource.

Authors

  • Adil Salhi
    King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, Saudi Arabia.
  • Magbubah Essack
    King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, Saudi Arabia.
  • Tanvir Alam
    College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.
  • Vladan P Bajic
    b VINCA Institute of Nuclear Sciences , Belgrade , Republic of Serbia.
  • Lina Ma
    c BIG Data Center, Beijing Institute of Genomics (BIG) , Chinese Academy of Sciences , Beijing , China.
  • Aleksandar Radovanovic
    a King Abdullah University of Science and Technology (KAUST) , Computational Bioscience Research Center (CBRC) , Thuwal , Kingdom of Saudi Arabia.
  • Benoit Marchand
    e New York University , Abu Dhabi , UAE.
  • Sebastian Schmeier
    f Massey University Auckland, Institute of Natural and Mathematical Sciences , Albany , Auckland , New Zealand.
  • Zhang Zhang
    c BIG Data Center, Beijing Institute of Genomics (BIG) , Chinese Academy of Sciences , Beijing , China.
  • Vladimir B Bajic
    King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, Saudi Arabia.