A graphical model for protein secondary structure prediction

@inproceedings{Chu2004AGM,
  title={A graphical model for protein secondary structure prediction},
  author={Wei Chu and Zoubin Ghahramani and David L. Wild},
  booktitle={ICML},
  year={2004}
}
In this paper, we present a graphical model for protein secondary structure prediction. This model extends segmental semi-Markov models (SSMM) to exploit multiple sequence alignment profiles which contain information from evolutionarily related sequences. A novel parameterized model is proposed as the likelihood function for the SSMM to capture the segmental conformation. By incorporating the information from long range interactions in ß-sheets, this model is capable of carrying out inference… CONTINUE READING
Highly Cited
This paper has 51 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 32 extracted citations

51 Citations

0510'07'10'13'16
Citations per Year
Semantic Scholar estimates that this publication has 51 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-8 of 8 references

Statistical models and monte carlo methods for protein structure prediction

  • C. S. Schmidler
  • Ph.D. thesis,
  • 2002
Highly Influential
4 Excerpts

Similar Papers

Loading similar papers…