miES: predicting the essentiality of miRNAs with machine learning and sequence features-Reference-Cited by-同舟云学术

miES: predicting the essentiality of miRNAs with machine learning and sequence features

Published:2018-08-28 Issue:6 Volume:35 Page:1053-1054
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Song Fei¹,Cui Chunmei²,Gao Lin¹,Cui Qinghua²³

Affiliation:

1. School of Computer Science and Technology, Xidian University, Xi'an, Shaanxi, China

2. Department of Biomedical Informatics, Center for Noncoding RNA Medicine, School of Basic Medical Sciences, Peking University, Beijing, China

3. Center of Bioinformatics, Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China

Funder

National Key R&D Program

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/35/6/1053/28079266/bty738.pdf

Reference14 articles.

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2. miRCarta: a central repository for collecting miRNA candidates;Backes;Nucleic Acids Res.,2018

3. Metazoan MicroRNAs;Bartel;Cell,2018

4. Non-coding RNAs in development and disease: background, mechanisms, and therapeutic approaches;Beermann;Physiol. Rev,2016

5. An integrated expression atlas of miRNAs and their promoters in human and mouse;de Rie;Nat. Biotechnol,2017

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