Progress of 1D protein structure prediction at last. NN which predicts protein secondary structure. Bridging the protein sequence-structure gap by structure predictions. Pitfalls of protein sequence analysis. Refining neural network predictions for helical transmembrane proteins by dynamic programming.
Protein fold recognition by prediction-based threading.
Learning from evolution to predict protein structure. Protein structures sustain evolutionary drift. Better 1D predictions by experts with machines. Marrying structure and genomics. A modified definition of SOV, a segment-based measure for protein secondary structure prediction assessment.