A human disease related miRNA prediction method. HDMP is based on weighted k most similar neighbors is presented for predicting disease miRNAs. Experiments validated that HDMP achieved significantly higher prediction performance than existing methods. In addition, the case studies examining prostatic neoplasms, breast neoplasms, and lung neoplasms, showed that HDMP can uncover potential disease miRNA candidates.
Key Laboratory of Database and Parallel Computing of Heilongjiang Province, School of Computer Science and Technology, Heilongjiang University, Harbin, China; School of Computer and Information Engineering, Harbin University of Commerce, Harbin, China; Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin, China; School of Information Science and Technology, Heilongjiang University, Harbin, China; Department of Electrical and Computer Engineering, University of Texas, San Antonio, TX, USA
HDMP funding source(s)
This work is supported by Natural Science Foundation of China (60932008 and 61172098), Natural Science Foundation of Heilongjiang Province (F201119), National Institute of Health (R01 CA096512), and Qatar National Research Fund (09-874-3-235).