A high level interface to SCOP and ASTRAL implemented in python.
BACKGROUND
Benchmarking algorithms in structural bioinformatics often involves the construction of datasets of proteins with given sequence and structural properties. The SCOP database is a manually curated structural classification which groups together proteins on the basis of structural similarity. The ASTRAL compendium provides non redundant subsets of SCOP domains on the basis of sequence similarity such that no two domains in a given subset share more than a defined degree of sequence similarity. Taken together these two resources provide a 'ground truth' for assessing structural bioinformatics algorithms. We present a small and easy to use API written in python to enable construction of datasets from these resources.


RESULTS
We have designed a set of python modules to provide an abstraction of the SCOP and ASTRAL databases. The modules are designed to work as part of the Biopython distribution. Python users can now manipulate and use the SCOP hierarchy from within python programs, and use ASTRAL to return sequences of domains in SCOP, as well as clustered representations of SCOP from ASTRAL.


CONCLUSIONS
The modules make the analysis and generation of datasets for use in structural genomics easier and more principled.
Casbon
James A
JA
Bioinformatics, Institute of Cell and Molecular Science, School of Medicine and Dentistry, Queen Mary, University of London, London EC1 6BQ, UK. j.a.casbon@qmul.ac.uk
Crooks
Gavin E
GE
Saqi
Mansoor A S
MA
D003628:Database Management Systems; D030562:Databases, Protein; D016247:Information Storage and Retrieval / Q000379:methods*; D011381:Programming Languages; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D017386:Sequence Homology, Amino Acid; D012984:Software; D014584:User-Computer Interface