CRNPRED: highly accurate prediction of one-dimensional protein structures by large-scale critical random networks

@article{Kinjo2006CRNPREDHA,
  title={CRNPRED: highly accurate prediction of one-dimensional protein structures by large-scale critical random networks},
  author={Akira R. Kinjo and Ken Nishikawa},
  journal={BMC Bioinformatics},
  year={2006},
  volume={7},
  pages={401 - 401}
}
One-dimensional protein structures such as secondary structures or contact numbers are useful for three-dimensional structure prediction and helpful for intuitive understanding of the sequence-structure relationship. Accurate prediction methods will serve as a basis for these and other purposes. We implemented a program CRNPRED which predicts secondary structures, contact numbers and residue-wise contact orders. This program is based on a novel machine learning scheme called critical random… CONTINUE READING

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