document: Modeling shape and topology of low-resolution density maps of biological macromolecules We develop an efficient way of representing the geometry and topology of volumetric datasets of biological structures from medium to low resolution , aiming at storing and querying them in a database framework . We make use of a new vector quantization algorithm to select the points within the macromolecule that best approximate the probability density function of the original volume data . Connectivity among points is obtained with the use of the alpha shapes theory . This novel data representation has a number of interesting characteristics , such as -LRB- 1 -RRB- it allows us to automatically segment and quantify a number of important structural features from low-resolution maps , such as cavities and channels , opening the possibility of querying large collections of maps on the basis of these quantitative structural features ; -LRB- 2 -RRB- it provides a compact representation in terms of size ; -LRB- 3 -RRB- it contains a subset of three-dimensional points that optimally quantify the densities of medium resolution data ; and -LRB- 4 -RRB- a general model of the geometry and topology of the macromolecule -LRB- as opposite to a spatially unrelated bunch of voxels -RRB- is easily obtained by the use of the alpha shapes theory
doc_bio_tags: B O O B O O O O O B I O O O O O O O O B O B O B I O B I O O O O O O O O O O O O O O B I O O O O O O O B I I O O O O O O O O O O O B I I O O B I I O B O O O O O O O O O B I I O O O B I O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O B O B O O O O O O O O O O O O O O O O B I O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O B I O O B O B O O O O O O O O O O O O O O O O O O O O O O B I I