Homology modelling by distance geometry

Secondary structure prediction for modelling by homology.

An improved method of secondary structure prediction has been developed to aid the modelling of proteins by homology. Selected data from four published algorithms are scaled and combined as a weighted mean to produce consensus algorithms. Each consensus algorithm is used to predict the secondary structure of a protein homologous to the target protein and of known structure. By comparison of the...

Recognizing protein folds by cluster distance geometry.

Cluster distance geometry is a recent generalization of distance geometry whereby protein structures can be described at even lower levels of detail than one point per residue. With improvements in the clustering technique, protein conformations can be summarized in terms of alternative contact patterns between clusters, where each cluster contains four sequentially adjacent amino acid residues...

Controlling Geometry of Homology Generators

Homology groups and their generators of a 2D image are computed using a hierarchical structure i.e. irregular graph pyramid. In this paper we show that the generators of the first homology groups of a 2D image, computed with this pyramid based method always fit on the borders of the regions.

Controlling Geometry of Homology Generators

Homology groups and their generators of a 2D image are computed using a hierarchical structure i.e. irregular graph pyramid. In this paper we show that the generators of the first homology groups of a 2D image, computed with this pyramid based method always fit on the boundaries of the regions.

Coarse Geometry and K-homology