Journal
BRIEFINGS IN BIOINFORMATICS
Volume 23, Issue 2, Pages -Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bib/bbac044
Keywords
microRNA; subcellular location; miRNA-mRNA interaction; random walk with restart; message passing
Funding
- Fundamental Research Funds for the Central Universities [050/ZJ21195006]
- Startup Foundation for Advanced Talent sat Nanjing Agricultural University [050/804009]
- National Natural Science Foundation of China [11901517]
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In this paper, a computational framework called MiRLoc is described for predicting the subcellular localization of miRNAs. Unlike existing methods, MiRLoc utilizes the functional similarity between miRNAs and incorporates information about the subcellular localization of target mRNAs, resulting in improved prediction performance.
Subcellular localization of microRNAs (miRNAs) is an important reflection of their biological functions. Considering the spatio-temporal specificity of miRNA subcellular localization, experimental detection techniques are expensive and time-consuming, which strongly motivates an efficient and economical computational method to predict miRNA subcellular localization. In this paper, we describe a computational framework, MiRLoc, to predict the subcellular localization of miRNAs. In contrast to existing methods, MiRLoc uses the functional similarity between miRNAs instead of sequence features and incorporates information about the subcellular localization of the corresponding target mRNAs. The results show that miRNA functional similarity data can be effectively used to predict miRNA subcellular localization, and that inclusion of subcellular localization information of target mRNAs greatly improves prediction performance.
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