检索结果-内蒙古大学图书馆

A study of different annealing schedules in SArna-predict A permutation based SA algorithm for rna folding

International Journal of Intelligent Computing and Cybernetics 2015年第2期8卷 152-171页

作者： Herbert H.Tsang Kay C.Wiese Applied Research Lab Trinity Western UniversityLangleyCanada School of Computing Science Simon Fraser UniversitySurreyCanada

Purpose–The purpose of this paper is to present a study of the effect of different types of annealing schedules for a ribonucleic acid(rna)secondary structure prediction algorithm based on simulated annealing(SA).Design/methodology/approach–An rna folding algorithm was implemented that assembles the final structure from potential substructures(helixes).structures are encoded as a permutation of *** SA searches this space of *** and annealing schedules were studied and fine-tuned to optimize algorithm ***–In comparing with mfold,the SA algorithm shows comparable results(in terms of F-measure)even with a less sophisticated thermodynamic *** terms of average specificity,the SA algorithm has provided surpassing *** limitations/implications–Most of the underlying thermodynamic models are too simplistic and incomplete to accurately model the free energy for larger *** is the largest limitation of free energy-based rna folding algorithms in *** implications–The algorithm offers a different approach that can be used in practice to fold rna sequences ***/value–The algorithm is one of only two SA-based rna folding *** authors use a very different encoding,based on permutation of candidate *** in depth study of annealing schedules and other parameters makes the algorithm a strong *** benefit is that new thermodynamic models can be incorporated with relative ease(which is not the case for algorithms based on dynamic programming).

关键词： Annealing schedule Simulated annealing rna secondary structure prediction Ribonucleic acid rna folding Permutation

来源：评论

学校读者我要写书评

暂无评论

Identification and characterization of novel conserved rna structures in Drosophila

引用

BMC GENOMICS 2018年第1期19卷 1-20页

作者： Kirsch, Rebecca Seemann, Stefan E. Ruzzo, Walter L. Cohen, Stephen M. Stadler, Peter F. Gorodkin, Jan Univ Copenhagen Ctr Noncoding RNA Technol & Hlth Gronnegardsvej 3 DK-1870 Frederiksberg C Denmark Univ Copenhagen Dept Vet & Anim Sci Gronnegardsvej 3 DK-1870 Frederiksberg C Denmark Univ Washington Sch Comp Sci & Engn Box 352350 Seattle WA 98195 USA Univ Washington Dept Genome Sci Box 355065 Seattle WA 98195 USA Fred Hutchinson Canc Res Ctr 1100 Fairview Ave Seattle WA 98109 USA Univ Copenhagen Dept Cellular & Mol Med Blegdamsvej 3 DK-2200 Copenhagen N Denmark Univ Leipzig Bioinformat Grp Dept Comp Sci Hartelstr 16-18 D-04107 Leipzig Germany Univ Leipzig Interdisciplinary Ctr Bioinformat Hartelstr 16-18 D-04107 Leipzig Germany Max Planck Inst Math Sci Inselstr 22 D-04103 Leipzig Germany Univ Nacl Colombia Fac Ciencias Ciudad Univ COL-111321 Bogota DC Colombia Univ Vienna Dept Theoret Chem Wahringer Str 17 A-1090 Vienna Austria Santa Fe Inst 1399 Hyde Pk Rd Santa Fe NM 87501 USA

BackgroundComparative genomics approaches have facilitated the discovery of many novel non-coding and structured rnas (ncrnas). The increasing availability of related genomes now makes it possible to systematically search for compensatory base changes - and thus for conserved secondary structures - even in genomic regions that are poorly alignable in the primary sequence. The wealth of available transcriptome data can add valuable insight into expression and possible function for new ncrna candidates. Earlier work identifying ncrnas in Drosophila melanogaster made use of sequence-based alignments and employed a sliding window approach, inevitably biasing identification toward rnas encoded in the more conserved parts of the *** search for conserved rna structures (CRSs) that may not be highly conserved in sequence and to assess the expression of CRSs, we conducted a genome-wide structural alignment screen of 27 insect genomes including D. melanogaster and integrated this with an extensive set of tiling array data. The structural alignment screen revealed approximate to 30,000 novel candidate CRSs at an estimated false discovery rate of less than 10%. With more than one quarter of all individual CRS motifs showing sequence identities below 60%, the predicted CRSs largely complement the findings of sliding window approaches applied previously. While a sixth of the CRSs were ubiquitously expressed, we found that most were expressed in specific developmental stages or cell lines. Notably, most statistically significant enrichment of CRSs were observed in pupae, mainly in exons of untranslated regions, promotors, enhancers, and long ncrnas. Interestingly, cell lines were found to express a different set of CRSs than were found in vivo. Only a small fraction of intergenic CRSs were co-expressed with the adjacent protein coding genes, which suggests that most intergenic CRSs are independent genetic *** study provides a more comprehensive view

关键词： Non-coding rna rna secondary structure prediction Drosophila melanogaster CMfinder Gene expression Development

来源：评论

学校读者我要写书评

暂无评论

Predicting rna secondary structures from sequence and probing data

引用

METHODS 2016年 103卷 86-98页

作者： Lorenz, Ronny Wolfinger, Michael T. Tanzer, Andrea Hofacker, Ivo L. Univ Vienna Fac Chem Dept Theoret Chem Wahringerstr 17 A-1090 Vienna Austria Med Univ Vienna Ctr Anat & Cell Biol Wahringerstr 13 A-1090 Vienna Austria Univ Vienna Fac Comp Sci Res Grp Bioinformat & Computat Biol Wahringerstr 29 A-1090 Vienna Austria

rna secondary structures have proven essential for understanding the regulatory functions performed by rna such as micrornas, bacterial small rnas, or riboswitches. This success is in part due to the availability of efficient computational methods for predicting rna secondary structures. Recent advances focus on dealing with the inherent uncertainty of prediction by considering the ensemble of possible structures rather than the single most stable one. Moreover, the advent of high-throughput structural probing has spurred the development of computational methods that incorporate such experimental data as auxiliary information. (C) 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license.

关键词： rna secondary structure prediction structure probing

来源：评论

学校读者我要写书评

暂无评论

Rapid ab initio prediction of rna pseudoknots via graph tree decomposition

引用

JOUrnaL OF MATHEMATICAL BIOLOGY 2008年第1-2期56卷 145-159页

作者： Zhao, Jizhen Malmberg, Russell L. Cai, Liming Univ Georgia Dept Comp Sci Athens GA 30602 USA Univ Georgia Dept Plant Biol Athens GA 30602 USA

The prediction of rna secondary structure including pseudoknots remains a challenge due to the intractable computation of the sequence conformation from nucleotide interactions under free energy models. Optimal algorithms often assume a restricted class for the predicted rna structures and yet still require a high-degree polynomial time complexity, which is too expensive to use. Heuristic methods may yield time-efficient algorithms but they do not guarantee optimality of the predicted structure. This paper introduces a new and efficient algorithm for the prediction of rna structure with pseudoknots for which the structure is not restricted. Novel prediction techniques are developed based on graph tree decomposition. In particular, based on a simplified energy model, stem overlapping relationships are defined with a graph, in which a specialized maximum independent set corresponds to the desired optimal structure. Such a graph is tree decomposable;dynamic programming over a tree decomposition of the graph leads to an efficient optimal algorithm. The final structure predictions are then based on re-ranking a list of suboptimal structures under a more comprehensive free energy model. The new algorithm is evaluated on a large number of rna sequence sets taken from diverse resources. It demonstrates overall sensitivity and specificity that outperforms or is comparable with those of previous optimal and heuristic algorithms yet it requires significantly less time than the compared optimal algorithms.

关键词： rna secondary structure prediction pseudoknot thermodynamic energy tree decomposition tree width maximum independent set

来源：评论

学校读者我要写书评

暂无评论

A permutation-based genetic algorithm for the rna folding problem: a critical look at selection strategies, crossover operators, and representation issues

引用

BIOSYSTEMS 2003年第1-2期72卷 29-41页

作者： Wiese, KC Glen, E Simon Fraser Univ Surrey BC V3T 2W1 Canada

This paper presents a Genetic Algorithm (GA) to predict the secondary structure of rna molecules, where the secondary structure is encoded as a permutation. More specifically, the proposed algorithm predicts which specific canonical base pairs will form hydrogen bonds and build helices, also known as stems. Since rna is involved in both transcription and translation and also has catalytic and structural roles in the cell, determining the structure of rna is of fundamental importance in helping to determine rna function. We introduce a GA where a permutation is used to encode the secondary structure of rna molecules. We discuss results on rna sequences of lengths 76, 210, 681, and 785 nucleotides and present several improvements to our algorithm. We show that the Keep-Best Reproduction operator has similar benefits as in the traveling salesman problem domain. In addition, a comparison of several crossover operators is provided. We also compare the results of the permutation-based GA with a binary GA, demonstrating the benefits of the newly proposed representation. (C) 2003 Elsevier Ireland Ltd. All rights reserved.

关键词： genetic algorithms rna secondary structure prediction genetic operators selection representation

来源：评论

学校读者我要写书评

暂无评论

NNDB: An Expanded Database of Nearest Neighbor Parameters for Predicting Stability of Nucleic Acid secondary structures

引用

JOUrnaL OF MOLECULAR BIOLOGY 2024年第17期436卷 168549页

作者： Mittal, Abhinav Turner, Douglas H. Mathews, David H. Univ Rochester Med Ctr Dept Biochem & Biophys Rochester NY 14642 USA Univ Rochester Med Ctr Ctr RNA Biol Rochester NY 14642 USA Univ Rochester Dept Chem Rochester NY 14627 USA

Nearest neighbor thermodynamic parameters are widely used for rna and DNA secondary structure prediction and to model thermodynamic ensembles of secondary structures. The Nearest Neighbor Database (NNDB) is a freely available web resource (https://***/NNDB) that provides the functional forms, parameter values, and example calculations. The NNDB provides the 1999 and 2004 set of rna folding nearest neighbor parameters. We expanded the database to include a set of DNA parameters and a set of rna parameters that includes m6A in addition to the canonical rna nucleobases. The site was redesigned using the Quarto open-source publishing system. A downloadable PDF version of the complete resource and downloadable sets of nearest neighbor parameters are available. (c) 2024 Elsevier Ltd. All rights reserved.

关键词： Nucleic Acid Folding Thermodynamics Nearest Neighbor Analysis rna secondary structure prediction

来源：评论

学校读者我要写书评

暂无评论

Comparative and integrative analysis of rna structural profiling data： current practices and emerging questions

引用

Frontiers of Electrical and Electronic Engineering in China 2017年第1期5卷 3-24页

作者： Krishna Choudhary Fei Deng Sharon Aviran Department of Biomedical Engineering and Genome Center University of California at Davis Davis CA 95616 USA

Background： structure profiling experiments provide single-nucleotide information on rna structure. Recent advances in chemistry combined with application of high-throughput sequencing have enabled structure profiling at transeriptome scale and in living cells, creating unprecedented opportunities for rna biology. Propelled by these experimental advances, massive data with ever-increasing diversity and complexity have been generated, which give rise to new challenges in interpreting and analyzing these data. Results： We review current practices in analysis of structure profiling data with emphasis on comparative and integrative analysis as well as highlight emerging questions. Comparative analysis has revealed structural patterns across transcriptomes and has become an integral component of recent profiling studies. Additionally, profiling data can be integrated into traditional structure prediction algorithms to improve prediction accuracy. Conclusions： To keep pace with experimental developments, methods to facilitate, enhance and refine such analyses are needed. Parallel advances in analysis methodology will complement profiling technologies and help them reach their full potential.

关键词： rna structure profiling high-throughput sequencing rna secondary structure prediction chemical structure probing SHAPE-Seq

来源：评论

学校读者我要写书评

暂无评论

Classification of rna sequences with pseudoknots using features based on partial sequences

Classification of RNA sequences with pseudoknots using featu...

引用

IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology CIBCB

作者： Tong, Kwok-Kit Cheung, Kwan-Yau Lee, Kin-Hong Leung, Kwong-Sak Chinese Univ Hong Kong Dept Comp Sci & Engn Shatin Hong Kong Peoples R China

ISBN: (纸本)9781479969265

Classification on pseudoknots existence is a challenging and meaningful problem in Bioinformatics. As predicting rna secondary structures with pseudoknots is NP-complete problem while predicting pseudoknot-free structures can be done in O(n(3)) time, if a preliminary pseudoknots existence classification of rna sequence can be done before the prediction, the classification result can enhance the efficiency of rna secondary structure prediction. In this paper, a classification of the existence of pseudoknots in an rna sequence is presented. A set of features have been chosen by partial sequence content and thousands of rna sequences with validated structures are used to train the classifier. Using a validated testing dataset, this classification method is shown to achieve a very good performance that the best result get 87% accuracy in 10-fold cross validation and around 75% accuracy in testing data. Moreover it may reveal how partial sequence content can affect the formation of pseudoknots.

关键词： rna secondary structure prediction pseudoknot classification

来源：评论

学校读者我要写书评

暂无评论

Characterizing pseudobase and predicting rna secondary structure with simple H-type pseudoknots based on dynamic programming 1

引用

3rd International Conference on Advanced Data Mining and Applications

作者： Namsrai, Oyun-Erdene Ryu, Kenn Ho Chungbuk Natl Univ Sch Elect & Comp Engn Database BioInformat Lab Cheongju 361763 Chungbuk South Korea

ISBN: (数字)9783540738718

ISBN: (纸本)9783540738701

rna is a unique biopolymer that has the ability to store genetic information, like DNA, but also can have a functional role in the cell, like protein. The function of an rna is determined by its sequence and structure, and the rna structure is to a large extent determined by rna's ability to form base pairs with itself. Most work has been done to predict structures that do not contain pseudoknots. Pseudoknots are usually excluded due to the hardness of examining all possible structures efficiently and model the energy correctly. In this paper we will present characterization of Pseudobase and then we will introduce an improved version of dynamic programming solution to find the conformation with the maximum number of base pairs. After then we will introduce an implementation of predicting H-type pseudoknots based on dynamic programming. Our algorithm called "Iterated Dynamic Programming" has better space and time complexity than the previously known algorithms. The algorithm has a worst case complexity of O(N-3) in time and O(N-2) in storage. In addition, our approach can be easily extended and applied to other classes of more general pseudoknots. Availability: The algorithm has been implemented in C++ in a program called "IDP", which is available at http://***/idp.

关键词： rna secondary structure prediction Pseudobase H-type pseudoknots dynamic programming

来源：评论

学校读者我要写书评

暂无评论

Predicting Consensus structures for rna Alignments Via Pseudo-Energy Minimization

引用

BIOINFORMATICS AND BIOLOGY INSIGHTS 2009年第3期3卷 51-69页

作者： Spirollari, Junilda Wang, Jason T. L. Zhang, Kaizhong Bellofatto, Vivian Park, Yongkyu Shapiro, Bruce A. New Jersey Inst Technol Dept Comp Sci Bioinformat Program Univ Hts Newark NJ 07102 USA Univ Med & Dent New Jersey New Jersey Med Sch Int Ctr Publ Hlth Dept Microbiol & Mol Genet Newark NJ 07103 USA Univ Western Ontario Dept Comp Sci London ON N6A 5B7 Canada Univ Med & Dent New Jersey New Jersey Med Sch Dept Cell Biol & Mol Med Newark NJ 07103 USA NCI Ctr Canc Res Nanobiol Program Frederick MD 21702 USA

Thermodynamic processes with free energy parameters are often used in algorithms that solve the free energy minimization problem to predict secondary structures of single rna sequences. While results from these algorithms are promising, an observation is that single sequence-based methods have moderate accuracy and more information is needed to improve on rna secondary structure prediction, such as covariance scores obtained from multiple sequence alignments. We present in this paper a new approach to predicting the consensus secondary structure of a set of aligned rna sequences via pseudo-energy minimization. Our tool, called RSpredict, takes into account sequence covariation and employs effective heuristics for accuracy improvement. RSpredict accepts, as input data, a multiple sequence alignment in FASTA or ClustalW format and outputs the consensus secondary structure of the input sequences in both the Vienna style Dot Bracket format and the Connectivity Table format. Our method was compared with some widely used tools including KNetFold, Pfold and rnaalifold. A comprehensive test on different datasets including Rfam sequence alignments and a multiple sequence alignment obtained from our study on the Drosophila X chromosome reveals that RSpredict is competitive with the existing tools on the tested datasets.

关键词： rna secondary structure prediction Drosophila secondary structure Rfam sequence alignments normalized energy

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：