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Structure Prediction: New Insights into Decrypting Long Noncoding RNAs

Key Laboratory for Space Bioscience & Biotechnology, Institute of Special Environmental Biophysics, School of Life Sciences, Northwestern Polytechnical University, 127 Youyi Xilu, Xi’an 710072, China
Department of Bone Disease Oncology, Hong-Hui Hospital, Xi’an Jiaotong University College of Medicine, South Door slightly Friendship Road 555, Xi’an 710054, China
Author to whom correspondence should be addressed.
Co-corresponding author.
Academic Editor: Martin Pichler
Int. J. Mol. Sci. 2016, 17(1), 132;
Received: 10 October 2015 / Revised: 18 December 2015 / Accepted: 12 January 2016 / Published: 21 January 2016
(This article belongs to the Collection Regulation by Non-Coding RNAs)
Long noncoding RNAs (lncRNAs), which form a diverse class of RNAs, remain the least understood type of noncoding RNAs in terms of their nature and identification. Emerging evidence has revealed that a small number of newly discovered lncRNAs perform important and complex biological functions such as dosage compensation, chromatin regulation, genomic imprinting, and nuclear organization. However, understanding the wide range of functions of lncRNAs related to various processes of cellular networks remains a great experimental challenge. Structural versatility is critical for RNAs to perform various functions and provides new insights into probing the functions of lncRNAs. In recent years, the computational method of RNA structure prediction has been developed to analyze the structure of lncRNAs. This novel methodology has provided basic but indispensable information for the rapid, large-scale and in-depth research of lncRNAs. This review focuses on mainstream RNA structure prediction methods at the secondary and tertiary levels to offer an additional approach to investigating the functions of lncRNAs. View Full-Text
Keywords: lncRNAs; function; structure prediction; secondary structure; tertiary structure lncRNAs; function; structure prediction; secondary structure; tertiary structure
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MDPI and ACS Style

Yan, K.; Arfat, Y.; Li, D.; Zhao, F.; Chen, Z.; Yin, C.; Sun, Y.; Hu, L.; Yang, T.; Qian, A. Structure Prediction: New Insights into Decrypting Long Noncoding RNAs. Int. J. Mol. Sci. 2016, 17, 132.

AMA Style

Yan K, Arfat Y, Li D, Zhao F, Chen Z, Yin C, Sun Y, Hu L, Yang T, Qian A. Structure Prediction: New Insights into Decrypting Long Noncoding RNAs. International Journal of Molecular Sciences. 2016; 17(1):132.

Chicago/Turabian Style

Yan, Kun, Yasir Arfat, Dijie Li, Fan Zhao, Zhihao Chen, Chong Yin, Yulong Sun, Lifang Hu, Tuanmin Yang, and Airong Qian. 2016. "Structure Prediction: New Insights into Decrypting Long Noncoding RNAs" International Journal of Molecular Sciences 17, no. 1: 132.

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