Literature DB >> 31884158

milRNApredictor: Genome-free prediction of fungi milRNAs by incorporating k-mer scheme and distance-dependent pair potential.

Yuangen Yao1, Huiyu Zhang2, Haiyou Deng2.   

Abstract

MicroRNA-like small RNAs (milRNAs) with length of 21-22 nucleotides are a type of small non-coding RNAs that are firstly found in Neurospora crassa in 2010. Identifying milRNAs of species without genomic information is a difficult problem. Here, knowledge-based energy features are developed to identify milRNAs by tactfully incorporating k-mer scheme and distance-dependent pair potential. Compared with k-mer scheme, features developed here can alleviate the inherent curse of dimensionality in k-scheme once k becomes large. In addition, milRNApredictor built on novel features performs comparably to k-mer scheme, and achieves sensitivity of 74.21%, and specificity of 75.72% based on 10-fold cross-validation. Furthermore, for novel miRNA prediction, there exists high overlap of results from milRNApredictor and state-of-the-art mirnovo. However, milRNApredictor is simpler to use with reduced requirements of input data and dependencies. Taken together, milRNApredictor can be used to de novo identify fungi milRNAs and other very short small RNAs of non-model organisms.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Knowledge-based energy feature; MiRNA; Prediction; Random forest; milRNA

Mesh:

Substances:

Year:  2019        PMID: 31884158     DOI: 10.1016/j.ygeno.2019.12.019

Source DB:  PubMed          Journal:  Genomics        ISSN: 0888-7543            Impact factor:   5.736


  2 in total

1.  PlantMirP2: An Accurate, Fast and Easy-To-Use Program for Plant Pre-miRNA and miRNA Prediction.

Authors:  Dashuai Fan; Yuangen Yao; Ming Yi
Journal:  Genes (Basel)       Date:  2021-08-21       Impact factor: 4.096

2.  RNA-Seq, Bioinformatic Identification of Potential MicroRNA-like Small RNAs in the Edible Mushroom Agaricus bisporus and Experimental Approach for Their Validation.

Authors:  Francisco R Marin; Alberto Dávalos; Dylan Kiltschewskij; Maria C Crespo; Murray Cairns; Eduardo Andrés-León; Cristina Soler-Rivas
Journal:  Int J Mol Sci       Date:  2022-04-28       Impact factor: 6.208

  2 in total

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