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  TPRpred: A tool for prediction of TPR-, PPR- and SELI-like repeats from protein sequences.

Karpenahalli, M. R., Lupas, A. N., & Söding, J. (2007). TPRpred: A tool for prediction of TPR-, PPR- and SELI-like repeats from protein sequences. BMC Bioinformatics, 8: 2. doi:10.1186/1471-2105-8-2.

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Karpenahalli, M. R.1, Author
Lupas, A. N.1, Author
Söding, J.2, Author           
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1external, ou_persistent22              
2Research Group of Computational Biology, MPI for Biophysical Chemistry, Max Planck Society, ou_1933286              

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 Abstract: Background Solenoid repeat proteins of the Tetratrico Peptide Repeat (TPR) family are involved as scaffolds in a broad range of protein-protein interactions. Several resources are available for the prediction of TPRs, however, they often fail to detect divergent repeat units. Results We have developed TPRpred, a profile-based method which uses a P-value-dependent score offset to include divergent repeat units and which exploits the tendency of repeats to occur in tandem. TPRpred detects not only TPR-like repeats, but also the related Pentatrico Peptide Repeats (PPRs) and SEL1-like repeats. The corresponding profiles were generated through iterative searches, by varying the threshold parameters for inclusion of repeat units into the profiles, and the best profiles were selected based on their performance on proteins of known structure. We benchmarked the performance of TPRpred in detecting TPR-containing proteins and in delineating the individual repeats therein, against currently available resources. Conclusion TPRpred performs significantly better in detecting divergent repeats in TPR-containing proteins, and finds more individual repeats than the existing methods. The web server is available at http://tprpred.tuebingen.mpg.de webcite, and the C++ and Perl sources of TPRpred along with the profiles can be downloaded from ftp://ftp.tuebingen.mpg.de/ebio/protevo/TPRpred/ webcite.

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Language(s): eng - English
 Dates: 2007-01-03
 Publication Status: Published online
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 Rev. Type: Peer
 Identifiers: DOI: 10.1186/1471-2105-8-2
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Title: BMC Bioinformatics
Source Genre: Journal
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Publ. Info: BioMed Central
Pages: - Volume / Issue: 8 Sequence Number: 2 Start / End Page: - Identifier: ISSN: 1471-2105
CoNE: https://pure.mpg.de/cone/journals/resource/111000136905000