DNAshape statistics

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Citations per year

Number of citations per year for the bioinformatics software tool DNAshape
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This map represents all the scientific publications referring to DNAshape per scientific context
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Protocols

DNAshape specifications

Information


Unique identifier OMICS_09340
Name DNAshape
Interface Web user interface
Restrictions to use None
Input data DNA sequence(s)
Input format FASTA
Computer skills Basic
Stability Stable
Maintained No

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Publication for DNAshape

DNAshape citations

 (19)
library_books

Comparison of discriminative motif optimization using matrix and DNA shape based models

2018
BMC Bioinformatics
PMCID: 5840810
PMID: 29510689
DOI: 10.1186/s12859-018-2104-7

[…] , –]. Recently there have been several studies showing that variations in DNA shape can influence TF binding affinity, and that those contributions may involve non-independence between positions [–]. DNAshape is a program that predicts DNA structural features in a high-throughput manner based on Monte Carlo simulations of DNA fragments []. The Genome Browser for DNA shape annotations (GBshape), a […]

library_books

A unified approach for quantifying and interpreting DNA shape readout by transcription factors

2018
Mol Syst Biol
PMCID: 5822049
PMID: 29472273
DOI: 10.15252/msb.20177902

[…] ch have the same value in the table) were left out separately. Linear regression on k‐mer tables is implemented in the program kMerLinearRegression.py. The shape tables were generated by querying the DNAshape webserver for all pentamer sequences (Zhou et al, ). […]

call_split

Systematic prediction of DNA shape changes due to CpG methylation explains epigenetic effects on protein–DNA binding

2018
PMCID: 5800008
PMID: 29409522
DOI: 10.1186/s13072-018-0174-4
call_split See protocol

[…] The methyl-DNAshape method derives DNA shape features of methylated DNA at nucleotide resolution, while considering the local sequence context. In a manner analogous to our DNAshape method for unmethylated DNA [ […]

call_split

Experimental maps of DNA structure at nucleotide resolution distinguish intrinsic from protein induced DNA deformations

2018
Nucleic Acids Res
PMCID: 5946862
PMID: 29390080
DOI: 10.1093/nar/gky033
call_split See protocol

[…] We found that minimally smoothing the ORChID2 pattern (both experimental and computed) made for easier comparison with minor groove width patterns from X-ray crystallography and from prediction by DNAshape (), and with each other. To smooth an expORChID2 or compORChID2 pattern we used the loess.smooth function in R, with parameters span = 0.015 and evaluation = 300, to smooth 300 nucleotides in […]

library_books

Expanding the repertoire of DNA shape features for genome scale studies of transcription factor binding

2017
Nucleic Acids Res
PMCID: 5728407
PMID: 29165643
DOI: 10.1093/nar/gkx1145

[…] shape information. Regardless of the source, structural information improved the accuracy of predictions of TF binding specificities. When we combined sequence with four shape features, acquired from DNAshape (pentamer), MC (tetramer), MD (tetramer) and XRC (tetramer), all provided significant improvements compared to 1mer sequence-only models. Given the consistency of our results, we conclude tha […]

library_books

Genome wide prediction of minor groove electrostatic potential enables biophysical modeling of protein–DNA binding

2017
Nucleic Acids Res
PMCID: 5716191
PMID: 29040720
DOI: 10.1093/nar/gkx915

[…] (,,–). However, NLPB calculations are computationally costly and cannot be used on massive or genome-scale DNA sequences. To infer minor-groove EP in a HT manner, we previously developed a HT method, DNAshape (), which enables prediction of MGW for massive experimental and computational data. Prediction results can be used to measure minor-groove EP somewhat indirectly, although correspondence bet […]


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DNAshape institution(s)
Molecular and Computational Biology Program, Department of Biological Sciences; Department of Physics and Astronomy; Department of Chemistry; Department of Computer Science; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA

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