miPEPPred-FRL: A Novel Method for Predicting Plant MiRNA-Encoded Peptides Using Adaptive Feature Representation Learning-Reference-Cited by-同舟云学术

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miPEPPred-FRL: A Novel Method for Predicting Plant MiRNA-Encoded Peptides Using Adaptive Feature Representation Learning

Published:2023-09-21 Issue: Volume: Page:
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Li Haibin¹,Meng Jun¹,Wang Zhaowei¹,Tang Youwei¹,Xia Shihao¹,Wang Yu¹,Qin Zhaojing¹,Luan Yushi²^ORCID

Affiliation:

1. School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning 116024, China

2. School of Bioengineering, Dalian University of Technology, Dalian, Liaoning 116024, China

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.3c01020

Reference47 articles.

1. MicroRNAs

2. Role of MicroRNAs in Plant and Animal Development

3. Transcriptional Control of Gene Expression by MicroRNAs

4. Primary transcripts of microRNAs encode regulatory peptides

5. vvi-miPEP172b and vvi-miPEP3635b increase cold tolerance of grapevine by regulating the corresponding MIRNA genes

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deciphering GB1’s Single Mutational Landscape: Insights from MuMi Analysis;The Journal of Physical Chemistry B;2024-08-08

2. Editorial: Machine Learning in Bio-cheminformatics;Journal of Chemical Information and Modeling;2024-04-08

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