A high level interface to SCOP and ASTRAL implemented in Python
<p>Abstract</p> <p>Background</p> <p>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 group...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2006-01-01
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| Series: | BMC Bioinformatics |
| Online Access: | http://www.biomedcentral.com/1471-2105/7/10 |
| Summary: | <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>The modules make the analysis and generation of datasets for use in structural genomics easier and more principled.</p> |
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| ISSN: | 1471-2105 |