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Accepted (AM)Open Access (License Unspecified), Open
Journal article
Progress and Current Challenges in Modeling Large RNAs
Journal of molecular biology, v 428(5), pp 736-747
27 Feb 2016
PMID: 26585404
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Recent breakthroughs in next-generation sequencing technologies have led to the discovery of several classes of non-coding RNAs (ncRNAs). It is now apparent that RNA molecules are not only just carriers of genetic information but also key players in many cellular processes. While there has been a rapid increase in the number of ncRNA sequences deposited in various databases over the past decade, the biological functions of these ncRNAs are largely not well understood. Similar to proteins, RNA molecules carry out a function by forming specific three-dimensional structures. Understanding the function of a particular RNA therefore requires a detailed knowledge of its structure. However, determining experimental structures of RNA is extremely challenging. In fact, RNA-only structures represent just 1% of the total structures deposited in the PDB. Thus, computational methods that predict three-dimensional RNA structures are in high demand. Computational models can provide valuable insights into structure–function relationships in ncRNAs and can aid in the development of functional hypotheses and experimental designs. In recent years, a set of diverse RNA structure prediction tools have become available, which differ in computational time, input data and accuracy. This review discusses the recent progress and challenges in RNA structure prediction methods.
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•Large RNAs are implicated as key players in many cellular processes.•Current progress in RNA tertiary structure prediction methods is reviewed.•Strategies for modeling large RNAs are discussed.
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Details
- Title
- Progress and Current Challenges in Modeling Large RNAs
- Creators
- Srinivas Somarowthu - Yale University
- Publication Details
- Journal of molecular biology, v 428(5), pp 736-747
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Biochemistry and Molecular Biology
- Web of Science ID
- WOS:000374072800002
- Scopus ID
- 2-s2.0-84961690111
- Other Identifier
- 991020837746604721
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- Web of Science research areas
- Biochemistry & Molecular Biology