Literature DB >> 24023366

A comparative evaluation on prediction methods of nucleosome positioning.

Hui Liu, Ruichang Zhang, Wei Xiong, Jihong Guan, Ziheng Zhuang, Shuigeng Zhou.   

Abstract

Nucleosome positioning plays an essential role in cellular processes by modulating accessibility of DNA to proteins. Many computational models have been developed to predict genome-wide nucleosome positions from DNA sequences. Comparative analysis of predicted and experimental nucleosome positioning maps facilitates understanding the regulatory mechanisms of transcription and DNA replication. Therefore, a comprehensive evaluation of existing computational methods is important and useful for biologists to choose appropriate ones in their research. In this article, we carried out a performance comparison among eight widely used computational methods on four species including yeast, fruitfly, mouse and human. In particular, we compared these methods on different regions of each species such as gene sequences, promoters and 5'UTR exons. The experimental results show that the performances of the two latest versions of the thermodynamic model are relatively steadier than the other four methods. Moreover, these methods are workable on four species, but their performances decrease gradually from yeast to human, indicating that the fundamental mechanism of nucleosome positioning is conserved through the evolution process, but more and more factors participate in the determination of nucleosome positions, which leads to sophisticated regulation mechanisms.
© The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  G:C content; nucleosomal sequence; nucleosome positioning; performance comparison; prediction accuracy

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Year:  2013        PMID: 24023366     DOI: 10.1093/bib/bbt062

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  14 in total

Review 1.  Nucleosome positioning in yeasts: methods, maps, and mechanisms.

Authors:  Corinna Lieleg; Nils Krietenstein; Maria Walker; Philipp Korber
Journal:  Chromosoma       Date:  2014-12-23       Impact factor: 4.316

2.  Incorporating chromatin accessibility data into sequence-to-expression modeling.

Authors:  Pei-Chen Peng; Md Abul Hassan Samee; Saurabh Sinha
Journal:  Biophys J       Date:  2015-03-10       Impact factor: 4.033

3.  Genomes of Multicellular Organisms Have Evolved to Attract Nucleosomes to Promoter Regions.

Authors:  Marco Tompitak; Cédric Vaillant; Helmut Schiessel
Journal:  Biophys J       Date:  2017-01-25       Impact factor: 4.033

4.  A deformation energy-based model for predicting nucleosome dyads and occupancy.

Authors:  Guoqing Liu; Yongqiang Xing; Hongyu Zhao; Jianying Wang; Yu Shang; Lu Cai
Journal:  Sci Rep       Date:  2016-04-07       Impact factor: 4.379

5.  Multiplexing Genetic and Nucleosome Positioning Codes: A Computational Approach.

Authors:  Behrouz Eslami-Mossallam; Raoul D Schram; Marco Tompitak; John van Noort; Helmut Schiessel
Journal:  PLoS One       Date:  2016-06-07       Impact factor: 3.240

6.  Benchmarking and refining probability-based models for nucleosome-DNA interaction.

Authors:  Marco Tompitak; Gerard T Barkema; Helmut Schiessel
Journal:  BMC Bioinformatics       Date:  2017-03-07       Impact factor: 3.169

7.  Nucleosomal signatures impose nucleosome positioning in coding and noncoding sequences in the genome.

Authors:  Sara González; Alicia García; Enrique Vázquez; Rebeca Serrano; Mar Sánchez; Luis Quintales; Francisco Antequera
Journal:  Genome Res       Date:  2016-09-23       Impact factor: 9.043

8.  The implication of DNA bending energy for nucleosome positioning and sliding.

Authors:  Guoqing Liu; Yongqiang Xing; Hongyu Zhao; Lu Cai; Jianying Wang
Journal:  Sci Rep       Date:  2018-06-11       Impact factor: 4.379

9.  Deep learning architectures for prediction of nucleosome positioning from sequences data.

Authors:  Mattia Di Gangi; Giosuè Lo Bosco; Riccardo Rizzo
Journal:  BMC Bioinformatics       Date:  2018-11-20       Impact factor: 3.169

10.  Divergent Residues Within Histone H3 Dictate a Unique Chromatin Structure in Saccharomyces cerevisiae.

Authors:  Kristina L McBurney; Andrew Leung; Jennifer K Choi; Benjamin J E Martin; Nicholas A T Irwin; Till Bartke; Christopher J Nelson; LeAnn J Howe
Journal:  Genetics       Date:  2015-11-03       Impact factor: 4.562

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