For a successful analysis of the relation between amino acid sequence and protein structure, an unambiguous and physically meaningful definition of secondary structure is essential. We have developed… (More)
With a rapidly growing pool of known tertiary structures, the importance of protein structure comparison parallels that of sequence alignment. We have developed a novel algorithm (DALI) for optimal… (More)
We have trained a two-layered feed-forward neural network on a non-redundant data base of 130 protein chains to predict the secondary structure of water-soluble proteins. A new key aspect is the use… (More)
The comparison of the three-dimensional shapes of protein molecules poses a complex algorithmic problem. Its solution provides biologists with computational tools to organize the rapidly growing set… (More)
The database of known protein three-dimensional structures can be significantly increased by the use of sequence homology, based on the following observations. (1) The database of known sequences,… (More)
Using evolutionary information contained in multiple sequence alignments as input to neural networks, secondary structure can be predicted at significantly increased accuracy. Here, we extend our… (More)
To reduce redundancy in the Protein Data Bank of 3D protein structures, which is caused by many homologous proteins in the data bank, we have selected a representative set of structures. The… (More)
Secondary structure prediction recently has surpassed the 70% level of average accuracy, evaluated on the single residue states helix, strand and loop (Q3). But the ultimate goal is reliable… (More)
Currently, the prediction of three-dimensional (3D) protein structure from sequence alone is an exceedingly difficult task. As an intermediate step, a much simpler task has been pursued extensively:… (More)