NDLI: Predicting miRNA’s target from primary structure by the nearest neighbor algorithm

Content Provider	Springer Nature Link
Author	Lin, Kao Qian, Ziliang Lu, Lin Lu, Lingyi Lai, Lihui Gu, Jieyi Zeng, Zhenbing Li, Haipeng Cai, Yudong
Copyright Year	2009
Abstract	We used a machine learning method, the nearest neighbor algorithm (NNA), to learn the relationship between miRNAs and their target proteins, generating a predictor which can then judge whether a new miRNA-target pair is true or not. We acquired 198 positive (true) miRNA-target pairs from Tarbase and the literature, and generated 4,888 negative (false) pairs through random combination. A 0/1 system and the frequencies of single nucleotides and di-nucleotides were used to encode miRNAs into vectors while various physicochemical parameters were used to encode the targets. The NNA was then applied, learning from these data to produce a predictor. We implemented minimum redundancy maximum relevance (mRMR) and properties forward selection (PFS) to reduce the redundancy of our encoding system, obtaining 91 most efficient properties. Finally, via the Jackknife cross-validation test, we got a positive accuracy of 69.2% and an overall accuracy of 96.0% with all the 253 properties. Besides, we got a positive accuracy of 83.8% and an overall accuracy of 97.2% with the 91 most efficient properties. A web-server for predictions is also made available at http://app3.biosino.org:8080/miRTP/index.jsp.
Starting Page	719
Ending Page	729
Page Count	11
File Format	PDF
ISSN	13811991
Journal	Molecular Diversity
Volume Number	14
Issue Number	4
e-ISSN	1573501X
Language	English
Publisher	Springer Netherlands
Publisher Date	2009-12-30
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	miRNA Target Predict Nearest neighbor algorithm Minimum redundancy maximum relevance Properties forward selection Pharmacy Polymer Sciences Organic Chemistry Biochemistry
Content Type	Text
Resource Type	Article
Subject	Organic Chemistry Medicine Drug Discovery Molecular Biology Physical and Theoretical Chemistry Information Systems Catalysis Inorganic Chemistry

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