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- W2007626265 endingPage "300" @default.
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- W2007626265 abstract "Accuracy of predicting protein secondary structure and solvent accessibility from sequence information has been improved significantly by using information contained in multiple sequence alignments as input to a neural network system. For the Asilomar meeting, predictions for 13 proteins were generated automatically using the publicly available prediction method PHD. The results confirm the estimate of 72% three-state prediction accuracy. The fairly accurate predictions of secondary structure segments made the tool useful as a starting point for modeling of higher dimensional aspects of protein structure." @default.
- W2007626265 created "2016-06-24" @default.
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- W2007626265 date "1995-11-01" @default.
- W2007626265 modified "2023-10-18" @default.
- W2007626265 title "Progress of 1D protein structure prediction at last" @default.
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- W2007626265 doi "https://doi.org/10.1002/prot.340230304" @default.
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