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. A platform for integrating threading results with protein family analyses. Effective use of sequence correlation and conservation in fold recognition.