Log in

Relevant bibliographies by topics / RNA structure / Journal articles

To see the other types of publications on this topic, follow the link: RNA structure.

Journal articles on the topic 'RNA structure'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'RNA structure.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Yamasaki, Satoshi, and Kazuhiko Fukui. "2P266 Tertiary structure prediction of RNA-RNA complex structures using secondary structure information(22A. Bioinformatics: Structural genomics,Poster)." Seibutsu Butsuri 53, supplement1-2 (2013): S203. http://dx.doi.org/10.2142/biophys.53.s203_1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Skeparnias, Ilias, and Jinwei Zhang. "Cooperativity and Interdependency between RNA Structure and RNA–RNA Interactions." Non-Coding RNA 7, no. 4 (2021): 81. http://dx.doi.org/10.3390/ncrna7040081.

Full text

Abstract:

Complex RNA–RNA interactions are increasingly known to play key roles in numerous biological processes from gene expression control to ribonucleoprotein granule formation. By contrast, the nature of these interactions and characteristics of their interfaces, especially those that involve partially or wholly structured RNAs, remain elusive. Herein, we discuss different modalities of RNA–RNA interactions with an emphasis on those that depend on secondary, tertiary, or quaternary structure. We dissect recently structurally elucidated RNA–RNA complexes including RNA triplexes, riboswitches, ribozy

APA, Harvard, Vancouver, ISO, and other styles

3

Conn, Graeme L., and David E. Draper. "RNA structure." Current Opinion in Structural Biology 8, no. 3 (1998): 278–85. http://dx.doi.org/10.1016/s0959-440x(98)80059-6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

WANG, ZHUOZHI, and KAIZHONG ZHANG. "MULTIPLE RNA STRUCTURE ALIGNMENT." Journal of Bioinformatics and Computational Biology 03, no. 03 (2005): 609–26. http://dx.doi.org/10.1142/s0219720005001296.

Full text

Abstract:

Ribonucleic Acid (RNA) structures can be viewed as a special kind of strings where characters in a string can bond with each other. The question of aligning two RNA structures has been studied for a while, and there are several successful algorithms that are based upon different models. In this paper, by adopting the model introduced in Wang and Zhang,19 we propose two algorithms to attack the question of aligning multiple RNA structures. Our methods are to reduce the multiple RNA structure alignment problem to the problem of aligning two RNA structure alignments. Meanwhile, we will show that

APA, Harvard, Vancouver, ISO, and other styles

5

Sabarinathan, Radhakrishnan, Christian Anthon, Jan Gorodkin, and Stefan Seemann. "Multiple Sequence Alignments Enhance Boundary Definition of RNA Structures." Genes 9, no. 12 (2018): 604. http://dx.doi.org/10.3390/genes9120604.

Full text

Abstract:

Self-contained structured domains of RNA sequences have often distinct molecular functions. Determining the boundaries of structured domains of a non-coding RNA (ncRNA) is needed for many ncRNA gene finder programs that predict RNA secondary structures in aligned genomes because these methods do not necessarily provide precise information about the boundaries or the location of the RNA structure inside the predicted ncRNA. Even without having a structure prediction, it is of interest to search for structured domains, such as for finding common RNA motifs in RNA-protein binding assays. The prec

APA, Harvard, Vancouver, ISO, and other styles

6

Wang, Xi-Wen, Chu-Xiao Liu, Ling-Ling Chen, and Qiangfeng Cliff Zhang. "RNA structure probing uncovers RNA structure-dependent biological functions." Nature Chemical Biology 17, no. 7 (2021): 755–66. http://dx.doi.org/10.1038/s41589-021-00805-7.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Fuller-Pace, Frances V. "RNA helicases: modulators of RNA structure." Trends in Cell Biology 4, no. 8 (1994): 271–74. http://dx.doi.org/10.1016/0962-8924(94)90210-0.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Yang, Chenchen, Hao Wu, Tao Shen, Kai Zou, and Siqi Sun. "PriFold: Biological Priors Improve RNA Secondary Structure Predictions." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 1 (2025): 950–58. https://doi.org/10.1609/aaai.v39i1.32080.

Full text

Abstract:

Predicting RNA secondary structures is crucial for understanding RNA function, designing RNA-based therapeutics, and studying molecular interactions within cells. Existing deep-learning-based methods for RNA secondary structure prediction have mainly focused on local structural properties, often overlooking the global characteristics and evolutionary features of RNA sequences. Guided by biological priors, we propose PriFold, incorporating two key innovations: 1) improving attention mechanism with pairing probabilities to utilize global pairing characteristics, and 2) implementing data augmenta

APA, Harvard, Vancouver, ISO, and other styles

9

Turner, D. H., N. Sugimoto, and S. M. Freier. "RNA Structure Prediction." Annual Review of Biophysics and Biophysical Chemistry 17, no. 1 (1988): 167–92. http://dx.doi.org/10.1146/annurev.bb.17.060188.001123.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Miao, Zhichao, Ryszard W. Adamiak, Marc-Frédérick Blanchet, et al. "RNA-PuzzlesRound II: assessment of RNA structure prediction programs applied to three large RNA structures." RNA 21, no. 6 (2015): 1066–84. http://dx.doi.org/10.1261/rna.049502.114.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Flamm, Chirstoph, Ivo L. Hofacker, and Peter F. Stadler. "RNA In Silico The Computational Biology of RNA Secondary Structures." Advances in Complex Systems 02, no. 01 (1999): 65–90. http://dx.doi.org/10.1142/s0219525999000059.

Full text

Abstract:

RNA secondary structures provide a unique computer model for investigating the most important aspects of structural and evolutionary biology. The existence of efficient algorithms for solving the folding problem, i.e., for predicting the secondary structure given only the sequence, allows the construction of realistic computer simulations. The notion of a "landscape" underlies both the structure formation (folding) and the (in vitro) evolution of RNA. Evolutionary adaptation may be seen as hill climbing process on a fitness landscape which is determined by the phenotype of the RNA molecule (wi

APA, Harvard, Vancouver, ISO, and other styles

12

Wang, Xunxun, Shixiong Yu, En Lou, Ya-Lan Tan, and Zhi-Jie Tan. "RNA 3D Structure Prediction: Progress and Perspective." Molecules 28, no. 14 (2023): 5532. http://dx.doi.org/10.3390/molecules28145532.

Full text

Abstract:

Ribonucleic acid (RNA) molecules play vital roles in numerous important biological functions such as catalysis and gene regulation. The functions of RNAs are strongly coupled to their structures or proper structure changes, and RNA structure prediction has been paid much attention in the last two decades. Some computational models have been developed to predict RNA three-dimensional (3D) structures in silico, and these models are generally composed of predicting RNA 3D structure ensemble, evaluating near-native RNAs from the structure ensemble, and refining the identified RNAs. In this review,

APA, Harvard, Vancouver, ISO, and other styles

13

Nie, Yuxin, Yuhong Zhang, and Jian Wu. "The Secondary Structure of Potato Spindle Tuber Viroid Determines Its Infectivity in Nicotiana benthamiana." Viruses 15, no. 12 (2023): 2307. http://dx.doi.org/10.3390/v15122307.

Full text

Abstract:

The function of RNAs is determined by their structure. However, studying the relationship between RNA structure and function often requires altering RNA sequences to modify the structures, which leads to the neglect of the importance of RNA sequences themselves. In our research, we utilized potato spindle tuber viroid (PSTVd), a circular-form non-coding infectious RNA, as a model with which to investigate the role of a specific rod-like structure in RNA function. By generating linear RNA transcripts with different start sites, we established 12 PSTVd forms with different secondary structures w

APA, Harvard, Vancouver, ISO, and other styles

14

Arslan, Abdullah N., Jithendar Anandan, Eric Fry, Keith Monschke, Nitin Ganneboina, and Jason Bowerman. "Efficient RNA structure comparison algorithms." Journal of Bioinformatics and Computational Biology 15, no. 06 (2017): 1740009. http://dx.doi.org/10.1142/s0219720017400091.

Full text

Abstract:

Recently proposed relative addressing-based ([Formula: see text]) RNA secondary structure representation has important features by which an RNA structure database can be stored into a suffix array. A fast substructure search algorithm has been proposed based on binary search on this suffix array. Using this substructure search algorithm, we present a fast algorithm that finds the largest common substructure of given multiple RNA structures in [Formula: see text] format. The multiple RNA structure comparison problem is NP-hard in its general formulation. We introduced a new problem for comparin

APA, Harvard, Vancouver, ISO, and other styles

15

Ahmad, Freed, Shahid Mahboob, Tahsin Gulzar, et al. "RNA-SSPT: RNA Secondary Structure Prediction Tools." Bioinformation 9, no. 17 (2013): 873–78. http://dx.doi.org/10.6026/97320630009873.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Evers, D., and R. Giegerich. "RNA movies: visualizing RNA secondary structure spaces." Bioinformatics 15, no. 1 (1999): 32–37. http://dx.doi.org/10.1093/bioinformatics/15.1.32.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Marchei, Daniele, and Emanuela Merelli. "RNA secondary structure factorization in prime tangles." BMC Bioinformatics 23, S6 (2022): 345. https://doi.org/10.1186/s12859-022-04879-5.

Full text

Abstract:

<strong>Background: </strong>Due to its key role in various biological processes, RNA secondary structures have always been the focus of in-depth analyses, with great efforts from mathematicians and biologists, to find a suitable abstract representation for modelling its functional and structural properties. One contribution is due to Kauffman and Magarshak, who modelled RNA secondary structures as mathematical objects <i>constructed</i> in link theory: <i>tangles of the Brauer Monoid</i>. In this paper, we extend the tangle-based model with its minimal prime factorization, useful to analyze p

APA, Harvard, Vancouver, ISO, and other styles

18

Zhang, Sicheng, Yi Cheng, Peixuan Guo, and Shi-Jie Chen. "VfoldMCPX: predicting multistrand RNA complexes." RNA 28, no. 4 (2022): 596–608. http://dx.doi.org/10.1261/rna.079020.121.

Full text

Abstract:

Multistrand RNA complexes play a critical role in RNA-related biological processes. The understanding of RNA functions and the rational design of RNA nanostructures require accurate prediction of the structure and folding stability of the complexes, including those containing pseudoknots. Here, we present VfoldMCPX, a new model for predicting two-dimensional (2D) structures and folding stabilities of multistrand RNA complexes. Based on a partition function-based algorithm combined with physical loop free energy parameters, the VfoldMCPX model predicts not only the native structure but also the

APA, Harvard, Vancouver, ISO, and other styles

19

Huang, Fenix, Christian Reidys, and Reza Rezazadegan. "Fatgraph models of RNA structure." Computational and Mathematical Biophysics 5, no. 1 (2017): 1–20. http://dx.doi.org/10.1515/mlbmb-2017-0001.

Full text

Abstract:

Abstract In this review paper we discuss fatgraphs as a conceptual framework for RNA structures. We discuss various notions of coarse-grained RNA structures and relate them to fatgraphs.We motivate and discuss the main intuition behind the fatgraph model and showcase its applicability to canonical as well as noncanonical base pairs. Recent discoveries regarding novel recursions of pseudoknotted (pk) configurations as well as their translation into context-free grammars for pk-structures are discussed. This is shown to allow for extending the concept of partition functions of sequences w.r.t. a

APA, Harvard, Vancouver, ISO, and other styles

20

Kulkarni, Mandar, Jayaraman Thangappan, Indrajit Deb, and Sangwook Wu. "Comparative analysis of RNA secondary structure accuracy on predicted RNA 3D models." PLOS ONE 18, no. 9 (2023): e0290907. http://dx.doi.org/10.1371/journal.pone.0290907.

Full text

Abstract:

RNA structure is conformationally dynamic, and accurate all-atom tertiary (3D) structure modeling of RNA remains challenging with the prevailing tools. Secondary structure (2D) information is the standard prerequisite for most RNA 3D modeling. Despite several 2D and 3D structure prediction tools proposed in recent years, one of the challenges is to choose the best combination for accurate RNA 3D structure prediction. Here, we benchmarked seven small RNA PDB structures (40 to 90 nucleotides) with different topologies to understand the effects of different 2D structure predictions on the accurac

APA, Harvard, Vancouver, ISO, and other styles

21

Carrascoza, Francisco, Maciej Antczak, Zhichao Miao, Eric Westhof, and Marta Szachniuk. "Evaluation of the stereochemical quality of predicted RNA 3D models in the RNA-Puzzles submissions." RNA 28, no. 2 (2021): 250–62. http://dx.doi.org/10.1261/rna.078685.121.

Full text

Abstract:

In silico prediction is a well-established approach to derive a general shape of an RNA molecule based on its sequence or secondary structure. This paper reports an analysis of the stereochemical quality of the RNA three-dimensional models predicted using dedicated computer programs. The stereochemistry of 1052 RNA 3D structures, including 1030 models predicted by fully automated and human-guided approaches within 22 RNA-Puzzles challenges and reference structures, is analyzed. The evaluation is based on standards of RNA stereochemistry that the Protein Data Bank requires from deposited experi

APA, Harvard, Vancouver, ISO, and other styles

22

Incarnato, Danny, Francesco Neri, Francesca Anselmi, and Salvatore Oliviero. "RNA structure framework: automated transcriptome-wide reconstruction of RNA secondary structures from high-throughput structure probing data." Bioinformatics 32, no. 3 (2015): 459–61. http://dx.doi.org/10.1093/bioinformatics/btv571.

Full text

APA, Harvard, Vancouver, ISO, and other styles

23

Li, Pan, Xiaolin Zhou, Kui Xu, and Qiangfeng Cliff Zhang. "RASP: an atlas of transcriptome-wide RNA secondary structure probing data." Nucleic Acids Research 49, no. D1 (2020): D183—D191. http://dx.doi.org/10.1093/nar/gkaa880.

Full text

Abstract:

Abstract RNA molecules fold into complex structures that are important across many biological processes. Recent technological developments have enabled transcriptome-wide probing of RNA secondary structure using nucleases and chemical modifiers. These approaches have been widely applied to capture RNA secondary structure in many studies, but gathering and presenting such data from very different technologies in a comprehensive and accessible way has been challenging. Existing RNA structure probing databases usually focus on low-throughput or very specific datasets. Here, we present a comprehen

APA, Harvard, Vancouver, ISO, and other styles

24

Chack, Aaron C., Emily B. Harrison, Caroline J. Aufgebauer, et al. "Abstract A023: RNA secondary structures mediate circular RNA stability and function." Molecular Cancer Therapeutics 23, no. 11_Supplement (2024): A023. http://dx.doi.org/10.1158/1538-8514.rnadrivers24-a023.

Full text

Abstract:

Abstract Our group recently discovered that the circular RNA (circRNA), CDR1as, promotes lung cancer metastasis in part through the stabilization of the coding gene, CDR1. The purpose of this study was to identify intramolecular RNA secondary structures of CDR1as and determine whether there is a functional relationship between the CDR1as secondary structure and non-small cell lung cancer (NSCLC) metastasis. We employed the chemical probing approach selective 2’- hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) to experimentally inform structure predictions o

APA, Harvard, Vancouver, ISO, and other styles

25

Seemann, Stefan E., Aashiq H. Mirza, Claus H. Bang-Berthelsen, et al. "Does rapid sequence divergence preclude RNA structure conservation in vertebrates?" Nucleic Acids Research 50, no. 5 (2022): 2452–63. http://dx.doi.org/10.1093/nar/gkac067.

Full text

Abstract:

Abstract Accelerated evolution of any portion of the genome is of significant interest, potentially signaling positive selection of phenotypic traits and adaptation. Accelerated evolution remains understudied for structured RNAs, despite the fact that an RNA’s structure is often key to its function. RNA structures are typically characterized by compensatory (structure-preserving) basepair changes that are unexpected given the underlying sequence variation, i.e., they have evolved through negative selection on structure. We address the question of how fast the primary sequence of an RNA can cha

APA, Harvard, Vancouver, ISO, and other styles

26

Brown, J. W., A. Birmingham, P. E. Griffiths, et al. "The RNA structure alignment ontology." RNA 15, no. 9 (2009): 1623–31. http://dx.doi.org/10.1261/rna.1601409.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

Kiening, Ochsenreiter, Hellinger, Rattei, Hofacker, and Frishman. "Conserved Secondary Structures in Viral mRNAs." Viruses 11, no. 5 (2019): 401. http://dx.doi.org/10.3390/v11050401.

Full text

Abstract:

RNA secondary structure in untranslated and protein coding regions has been shown to play an important role in regulatory processes and the viral replication cycle. While structures in non-coding regions have been investigated extensively, a thorough overview of the structural repertoire of protein coding mRNAs, especially for viruses, is lacking. Secondary structure prediction of large molecules, such as long mRNAs remains a challenging task, as the contingent of structures a sequence can theoretically fold into grows exponentially with sequence length. We applied a structure prediction pipel

APA, Harvard, Vancouver, ISO, and other styles

28

Yang, Heng, Renzhi Chen, and Ke Li. "Bridging Sequence-Structure Alignment in RNA Foundation Models." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 20 (2025): 21929–37. https://doi.org/10.1609/aaai.v39i20.35500.

Full text

Abstract:

The alignment between RNA sequences and structures in foundation models (FMs) has yet to be thoroughly investigated. Existing FMs have struggled to establish sequence-structure alignment, hindering the seamless flow of genomic information between RNA sequences and structures. In this study, we introduce OmniGenome, an RNA FM trained to align RNA sequences with respect to secondary structures through structure-contextualized modelling. This alignment enables free and bidirectional mappings between sequences and structures by utilizing a flexible RNA modelling paradigm that supports versatile in

APA, Harvard, Vancouver, ISO, and other styles

29

Grass, Lena M., Jan Wollenhaupt, Tatjana Barthel, et al. "Large-scale ratcheting in a bacterial DEAH/RHA-type RNA helicase that modulates antibiotics susceptibility." Proceedings of the National Academy of Sciences 118, no. 30 (2021): e2100370118. http://dx.doi.org/10.1073/pnas.2100370118.

Full text

Abstract:

Many bacteria harbor RNA-dependent nucleoside-triphosphatases of the DEAH/RHA family, whose molecular mechanisms and cellular functions are poorly understood. Here, we show that the Escherichia coli DEAH/RHA protein, HrpA, is an ATP-dependent 3 to 5′ RNA helicase and that the RNA helicase activity of HrpA influences bacterial survival under antibiotics treatment. Limited proteolysis, crystal structure analysis, and functional assays showed that HrpA contains an N-terminal DEAH/RHA helicase cassette preceded by a unique N-terminal domain and followed by a large C-terminal region that modulates

APA, Harvard, Vancouver, ISO, and other styles

30

Higgs, Paul G. "RNA secondary structure: physical and computational aspects." Quarterly Reviews of Biophysics 33, no. 3 (2000): 199–253. http://dx.doi.org/10.1017/s0033583500003620.

Full text

Abstract:

1. Background to RNA structure 2001.1 Types of RNA 2001.1.1 Transfer RNA (tRNA) 2001.1.2 Messenger RNA (mRNA) 2011.1.3 Ribosomal RNA (rRNA) 2011.1.4 Other ribonucleoprotein particles 2021.1.5 Viruses and viroids 2021.1.6 Ribozymes 2021.2 Elements of RNA secondary structure 2031.3 Secondary structure versus tertiary structure 2052. Theoretical and computational methods for RNA secondary structure determination 2082.1 Dynamic programming algorithms 2082.2 Kinetic folding algorithms 2102.3 Genetic algorithms 2122.4 Comparative methods 2133. RNA thermodynamics and folding mechanisms 2163.1 The rel

APA, Harvard, Vancouver, ISO, and other styles

31

Marti-Renom, Marc, and Emidio Capriotti. "Computational RNA Structure Prediction." Current Bioinformatics 3, no. 1 (2008): 32–45. http://dx.doi.org/10.2174/157489308783329823.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

Nawy, Tal. "RNA structure from sequence." Nature Methods 13, no. 6 (2016): 465. http://dx.doi.org/10.1038/nmeth.3892.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

Rossmann, M. G., and J. E. Johnson. "Icosahedral RNA Virus Structure." Annual Review of Biochemistry 58, no. 1 (1989): 533–69. http://dx.doi.org/10.1146/annurev.bi.58.070189.002533.

Full text

APA, Harvard, Vancouver, ISO, and other styles

34

Zlotorynski, Eytan. "m6A modulates RNA structure." Nature Reviews Molecular Cell Biology 16, no. 4 (2015): 204. http://dx.doi.org/10.1038/nrm3974.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Liszewski, Kathy. "Deciphering RNA Secondary Structure." Genetic Engineering & Biotechnology News 33, no. 18 (2013): 1, 26–28. http://dx.doi.org/10.1089/gen.33.18.09.

Full text

APA, Harvard, Vancouver, ISO, and other styles

36

Doudna, Jennifer A., and Jamie H. Cate. "RNA structure: crystal clear?" Current Opinion in Structural Biology 7, no. 3 (1997): 310–16. http://dx.doi.org/10.1016/s0959-440x(97)80045-0.

Full text

APA, Harvard, Vancouver, ISO, and other styles

37

Felden, Brice. "RNA structure: experimental analysis." Current Opinion in Microbiology 10, no. 3 (2007): 286–91. http://dx.doi.org/10.1016/j.mib.2007.05.001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Jossinet, Fabrice, Thomas E. Ludwig, and Eric Westhof. "RNA structure: bioinformatic analysis." Current Opinion in Microbiology 10, no. 3 (2007): 279–85. http://dx.doi.org/10.1016/j.mib.2007.05.010.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Vinson, V. "BIOCHEMISTRY: RNA Structure Conservation." Science 287, no. 5460 (2000): 1889a—1889. http://dx.doi.org/10.1126/science.287.5460.1889a.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Nowakowski, Jacek, and Ignacio Tinoco. "RNA Structure and Stability." Seminars in Virology 8, no. 3 (1997): 153–65. http://dx.doi.org/10.1006/smvy.1997.0118.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

Smola, Matthew J., Thomas W. Christy, Kaoru Inoue, et al. "SHAPE reveals transcript-wide interactions, complex structural domains, and protein interactions across the Xist lncRNA in living cells." Proceedings of the National Academy of Sciences 113, no. 37 (2016): 10322–27. http://dx.doi.org/10.1073/pnas.1600008113.

Full text

Abstract:

The 18-kb Xist long noncoding RNA (lncRNA) is essential for X-chromosome inactivation during female eutherian mammalian development. Global structural architecture, cell-induced conformational changes, and protein–RNA interactions within Xist are poorly understood. We used selective 2′-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) to examine these features of Xist at single-nucleotide resolution both in living cells and ex vivo. The Xist RNA forms complex well-defined secondary structure domains and the cellular environment strongly modulates the RNA stru

APA, Harvard, Vancouver, ISO, and other styles

42

Backofen, Rolf, Gad M. Landau, Mathias Möhl, Dekel Tsur, and Oren Weimann. "Fast RNA structure alignment for crossing input structures." Journal of Discrete Algorithms 9, no. 1 (2011): 2–11. http://dx.doi.org/10.1016/j.jda.2010.07.004.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Biebricher, Christof K. "The role of RNA structure in RNA replication." Berichte der Bunsengesellschaft für physikalische Chemie 98, no. 9 (1994): 1122–26. http://dx.doi.org/10.1002/bbpc.19940980908.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Xu, Xiaojun, and Shi-Jie Chen. "VfoldCPX Server for RNA/RNA Complex Structure Prediction." Biophysical Journal 110, no. 3 (2016): 410a. http://dx.doi.org/10.1016/j.bpj.2015.11.2213.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Vorobeva, M. A., D. A. Skvortsov, and D. D. Pervouchine. "Cooperation and Competition of RNA Secondary Structure and RNA–Protein Interactions in the Regulation of Alternative Splicing." Acta Naturae 15, no. 4 (2024): 23–31. http://dx.doi.org/10.32607/actanaturae.26826.

Full text

Abstract:

The regulation of alternative splicing in eukaryotic cells is carried out through the coordinated action of a large number of factors, including RNA-binding proteins and RNA structure. The RNA structure influences alternative splicing by blocking cis-regulatory elements, or bringing them closer or farther apart. In combination with RNA-binding proteins, it generates transcript conformations that help to achieve the necessary splicing outcome. However, the binding of regulatory proteins depends on RNA structure and, vice versa, the formation of RNA structure depends on the interaction with regu

APA, Harvard, Vancouver, ISO, and other styles

46

Shao, Yanqiu, and Qiangfeng Cliff Zhang. "Targeting RNA structures in diseases with small molecules." Essays in Biochemistry 64, no. 6 (2020): 955–66. http://dx.doi.org/10.1042/ebc20200011.

Full text

Abstract:

Abstract RNA is crucial for gene expression and regulation. Recent advances in understanding of RNA biochemistry, structure and molecular biology have revealed the importance of RNA structure in cellular processes and diseases. Various approaches to discovering drug-like small molecules that target RNA structure have been developed. This review provides a brief introduction to RNA structural biology and how RNA structures function as disease regulators. We summarize approaches to targeting RNA with small molecules and highlight their advantages, shortcomings and therapeutic potential.

APA, Harvard, Vancouver, ISO, and other styles

47

Gong, Sha, Chengxin Zhang, and Yang Zhang. "RNA-align: quick and accurate alignment of RNA 3D structures based on size-independent TM-scoreRNA." Bioinformatics 35, no. 21 (2019): 4459–61. http://dx.doi.org/10.1093/bioinformatics/btz282.

Full text

Abstract:

Abstract Motivation Comparison of RNA 3D structures can be used to infer functional relationship of RNA molecules. Most of the current RNA structure alignment programs are built on size-dependent scales, which complicate the interpretation of structure and functional relations. Meanwhile, the low speed prevents the programs from being applied to large-scale RNA structural database search. Results We developed an open-source algorithm, RNA-align, for RNA 3D structure alignment which has the structure similarity scaled by a size-independent and statistically interpretable scoring metric. Large-s

APA, Harvard, Vancouver, ISO, and other styles

48

Zhang, Chengxin, and Anna Marie Pyle. "CSSR: assignment of secondary structure to coarse-grained RNA tertiary structures." Acta Crystallographica Section D Structural Biology 78, no. 4 (2022): 466–71. http://dx.doi.org/10.1107/s2059798322001292.

Full text

Abstract:

RNA secondary-structure (rSS) assignment is one of the most routine forms of analysis of RNA 3D structures. However, traditional rSS assignment programs require full-atomic structures of the individual RNA nucleotides. This prevents their application to the modeling of RNA structures in which base atoms are missing. To address this issue, Coarse-grained Secondary Structure of RNA (CSSR), an algorithm for the assignment of rSS for structures in which nucleobase atomic positions are incomplete, has been developed. Using CSSR, an rSS assignment accuracy of ∼90% is achieved even for RNA structures

APA, Harvard, Vancouver, ISO, and other styles

49

Li, Hengwu, Daming Zhu, Caiming Zhang, Huijian Han, and Keith A. Crandall. "Characteristics and Prediction of RNA Structure." BioMed Research International 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/690340.

Full text

Abstract:

RNA secondary structures with pseudoknots are often predicted by minimizing free energy, which is NP-hard. Most RNAs fold during transcription from DNA into RNA through a hierarchical pathway wherein secondary structures form prior to tertiary structures. Real RNA secondary structures often have local instead of global optimization because of kinetic reasons. The performance of RNA structure prediction may be improved by considering dynamic and hierarchical folding mechanisms. This study is a novel report on RNA folding that accords with the golden mean characteristic based on the statistical

APA, Harvard, Vancouver, ISO, and other styles

50

Herbert, Austin, Abigail Hatfield, and Lela Lackey. "How does precursor RNA structure influence RNA processing and gene expression?" Bioscience Reports, January 23, 2023. http://dx.doi.org/10.1042/bsr20220149.

Full text

Abstract:

RNA is a fundamental biomolecule that has many purposes within cells. Due to its single-stranded and flexible nature, RNA naturally folds into complex and dynamic structures. Recent technological and computational advances have produced an explosion of RNA structural data. Many RNA structures clearly have regulatory and functional properties. Studying the structure of nascent RNAs is particularly challenging due to their low abundance and long length, but their structures are important because they can influence RNA processing. Precursor RNA processing is a nexus of pathways that determines ma

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!