Predicting protein secondary structure and solvent accessibility with an improved multiple linear regression method.

@article{Qin2005PredictingPS,
  title={Predicting protein secondary structure and solvent accessibility with an improved multiple linear regression method.},
  author={Sanbo Qin and Yun He and Xian-Ming Pan},
  journal={Proteins},
  year={2005},
  volume={61 3},
  pages={473-80}
}
We have improved the multiple linear regression (MLR) algorithm for protein secondary structure prediction by combining it with the evolutionary information provided by multiple sequence alignment of PSI-BLAST. On the CB513 dataset, the three states average overall per-residue accuracy, Q(3), reached 76.4%, while segment overlap accuracy, SOV99, reached 73.2%, using a rigorous jackknife procedure and the strictest reduction of eight states DSSP definition to three states. This represents an… CONTINUE READING

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A novel method for protein secondary structure prediction using dual - layer SVM and profiles

J Guo, Z Sun, Y Lin
Proteins • 2004

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