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Open Access Software

XSTREAM: A practical algorithm for identification and architecture modeling of tandem repeats in protein sequences

Aaron M Newman1 and James B Cooper12*

Author Affiliations

1 Biomolecular Science and Engineering Program, University of California, Santa Barbara, CA 93106, USA

2 Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA 93106, USA

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BMC Bioinformatics 2007, 8:382  doi:10.1186/1471-2105-8-382

Published: 11 October 2007

Abstract

Background

Biological sequence repeats arranged in tandem patterns are widespread in DNA and proteins. While many software tools have been designed to detect DNA tandem repeats (TRs), useful algorithms for identifying protein TRs with varied levels of degeneracy are still needed.

Results

To address limitations of current repeat identification methods, and to provide an efficient and flexible algorithm for the detection and analysis of TRs in protein sequences, we designed and implemented a new computational method called XSTREAM. Running time tests confirm the practicality of XSTREAM for analyses of multi-genome datasets. Each of the key capabilities of XSTREAM (e.g., merging, nesting, long-period detection, and TR architecture modeling) are demonstrated using anecdotal examples, and the utility of XSTREAM for identifying TR proteins was validated using data from a recently published paper.

Conclusion

We show that XSTREAM is a practical and valuable tool for TR detection in protein and nucleotide sequences at the multi-genome scale, and an effective tool for modeling TR domains with diverse architectures and varied levels of degeneracy. Because of these useful features, XSTREAM has significant potential for the discovery of naturally-evolved modular proteins with applications for engineering novel biostructural and biomimetic materials, and identifying new vaccine and diagnostic targets.