Email updates

Keep up to date with the latest news and content from BMC Bioinformatics and BioMed Central.

Open Access Research article

Analysis of superfamily specific profile-profile recognition accuracy

James A Casbon and Mansoor AS Saqi*

Author Affiliations

Bioinformatics Group, Centre for Infectious Disease, Institute of Cell and Molecular Science, Queen Mary's School of Medicine and Dentistry, University of London, 32 Newark St, London E1 2AA, UK

For all author emails, please log on.

BMC Bioinformatics 2004, 5:200  doi:10.1186/1471-2105-5-200

Published: 16 December 2004

Abstract

Background

Annotation of sequences that share little similarity to sequences of known function remains a major obstacle in genome annotation. Some of the best methods of detecting remote relationships between protein sequences are based on matching sequence profiles. We analyse the superfamily specific performance of sequence profile-profile matching. Our benchmark consists of a set of 16 protein superfamilies that are highly diverse at the sequence level. We relate the performance to the number of sequences in the profiles, the profile diversity and the extent of structural conservation in the superfamily.

Results

The performance varies greatly between superfamilies with the truncated receiver operating characteristic, ROC10, varying from 0.95 down to 0.01. These large differences persist even when the profiles are trimmed to approximately the same level of diversity.

Conclusions

Although the number of sequences in the profile (profile width) and degree of sequence variation within positions in the profile (profile diversity) contribute to accurate detection there are other superfamily specific factors.