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OMIT: Domain Ontology and Knowledge Acquisition in MicroRNA Target Prediction

(Short Paper)
  • Christopher Townsend
  • Jingshan Huang
  • Dejing Dou
  • Shivraj Dalvi
  • Patrick J. Hayes
  • Lei He
  • Wen-chang Lin
  • Haishan Liu
  • Robert Rudnick
  • Hardik Shah
  • Hao Sun
  • Xiaowei Wang
  • Ming Tan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6427)

Abstract

The identification and characterization of important roles microRNAs (miRNAs) played in human cancer is an increasingly active area in medical informatics. In particular, the prediction of miRNA target genes remains a challenging task to cancer researchers. Current efforts have focused on manual knowledge acquisition from existing miRNA databases, which is time-consuming, error-prone, and subject to biologists’ limited prior knowledge. Therefore, an effective knowledge acquisition has been inhibited. We propose a computing framework based on the Ontology for MicroRNA Target Prediction (OMIT), the very first ontology in miRNA domain. With such formal knowledge representation, it is thus possible to facilitate knowledge discovery and sharing from existing sources. Consequently, the framework aims to assist biologists in unraveling important roles of miRNAs in human cancer, and thus to help clinicians in making sound decisions when treating cancer patients.

Keywords

Resource Description Framework MicroRNA Target Prediction Formal Knowledge Representation Directed Acyclic Graph Model Limited Prior Knowledge 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Christopher Townsend
    • 1
  • Jingshan Huang
    • 1
  • Dejing Dou
    • 2
  • Shivraj Dalvi
    • 1
  • Patrick J. Hayes
    • 3
  • Lei He
    • 4
  • Wen-chang Lin
    • 5
  • Haishan Liu
    • 2
  • Robert Rudnick
    • 1
  • Hardik Shah
    • 1
  • Hao Sun
    • 6
  • Xiaowei Wang
    • 7
  • Ming Tan
    • 8
  1. 1.School of Computer and Information SciencesUniversity of South AlabamaMobileU.S.A.
  2. 2.Computer and Information Science DepartmentUniversity of OregonEugeneU.S.A.
  3. 3.Florida Institute for Human and Machine CognitionPensacolaU.S.A.
  4. 4.College of Science and TechnologyArmstrong Atlantic State UniversitySavannahU.S.A.
  5. 5.Institute of Biomedical Sciences Academia SinicaTaipeiTaiwan
  6. 6.Department of Chemical PathologyChinese University of Hong KongHong Kong, China
  7. 7.Department of Radiation OncologyWashington University School of MedicineSt. LouisU.S.A.
  8. 8.Mitchell Cancer InstituteUniversity of South AlabamaMobileU.S.A.

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