A Hopfield Neural Classifier and Its FPGA Implementation for Identification of Symmetrically Structured DNA Motifs

@article{Stepanova2007AHN,
  title={A Hopfield Neural Classifier and Its FPGA Implementation for Identification of Symmetrically Structured DNA Motifs},
  author={Maria Stepanova and Feng Lin and Valerie C.-L. Lin},
  journal={VLSI Signal Processing},
  year={2007},
  volume={48},
  pages={239-254}
}
Some specialized transcription factors recognize specific DNA sequences arranged in inverted and direct repeats with a short nucleotide spacer in between. Identification of these motifs has been challenging due to their high divergence. In this paper, we describe a novel computational approach that can greatly improve the efficiency and accuracy in prediction of these DNA binding sites. A Hopfield neural classifier was designed with the flexibility of internal structure being adapted… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 36 references

P

  • S. Jones
  • van Heyningen, H. M. Berman and J. M. Thornton…
  • 1999
Highly Influential
7 Excerpts

and J

  • A. Ormond
  • Rajapakse, BFPGA Implementations of Neural…
  • 2006
2 Excerpts

A Method for Discovering Transcription Factor Binding Sites with Improved Specificity ^

  • G. D. Stormo, B ANN-Spec
  • Pac . Symp . Biocomput
  • 2005

BNuclear Receptor Coactivators: The Key To Unlock Chromatin,^ Biochem

  • W. Xu
  • Cell. Biol., vol. 83, no. 4,
  • 2005
1 Excerpt

Similar Papers

Loading similar papers…