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motifStack for the analysis of transcription factor binding site evolution

Nature Methods volume 15, pages 8–9 (2018)Cite this article

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A sequence motif is a short recurring pattern with biological significance such as a DNA-recognition sequence for a transcription factor (TF), an mRNA splicing signal, or a functional region of a protein domain. Many high-throughput experimental approaches and computational tools have been developed to discover motifs from a population of functional sequences such as TF binding sites1. TF binding motifs are often represented as position weight matrices (PWMs) and visualized as sequence logos (Supplementary Note).

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Figure 1: Effects of experimental and computational methods on motif clustering.

References

  1. Das, M.K. & Dai, H.-K. BMC Bioinformatics 8, S21 (2007).

    Article  Google Scholar 

  2. Mahony, S. & Benos, P.V. Nucleic Acids Res. 35, W253–W258 (2007).

    Article  Google Scholar 

  3. Gupta, S., Stamatoyannopoulos, J.A., Bailey, T.L. & Noble, W.S. Genome Biol. 8, R24 (2007).

    Article  Google Scholar 

  4. Zhao, G. et al. G3 2, 469–481 (2012).

    Article  CAS  Google Scholar 

  5. Nettling, M. et al. BMC Bioinformatics 16, 387 (2015).

    Article  Google Scholar 

  6. Shannon, P. et al. Genome Res. 13, 2498–2504 (2003).

    Article  CAS  Google Scholar 

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Acknowledgements

We appreciate M. Enuameh and L. Ni for helpful discussion. S.A.W., M.H.B., and L.J.Z. were partly supported by National Human Genome Research Institute of the National Institutes of Health (R01HG004744-01).

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Authors and Affiliations

  1. Department of Molecular, Cell and Cancer Biology, University of Massachusetts Medical School, Worcester, Massachusetts, USA

    Jianhong Ou, Scot A Wolfe, Michael H Brodsky & Lihua Julie Zhu

  2. Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, Massachusetts, USA

    Scot A Wolfe

  3. Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts, USA

    Michael H Brodsky & Lihua Julie Zhu

  4. Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, USA

    Lihua Julie Zhu

Authors
  1. Jianhong Ou
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  2. Scot A Wolfe
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  3. Michael H Brodsky
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  4. Lihua Julie Zhu
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Corresponding authors

Correspondence to Michael H Brodsky or Lihua Julie Zhu.

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The authors declare no competing financial interests.

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Supplementary Figures 1–7 and Supplementary Note 1 (PDF 48697 kb)

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Ou, J., Wolfe, S., Brodsky, M. et al. motifStack for the analysis of transcription factor binding site evolution. Nat Methods 15, 8–9 (2018). https://doi.org/10.1038/nmeth.4555

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