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Nucleic Acids Research, 2003, Vol. 31, No. 13 3642-3644
© 2003 Oxford University Press

Static benchmarking of membrane helix predictions

Andrew Kernytsky*,1 and Burkhard Rost1,2,3

1 CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, 650 West 168th Street BB217, New York, NY 10032, USA 2 Columbia University Center for Computational Biology and Bioinformatics (C2B2), Russ Berrie Pavilion, 1150 St Nicholas Avenue, New York, NY 10032, USA 3 North East Structural Genomics Consortium (NESG), Department of Biochemistry and Molecular Biophysics, Columbia University, 650 West 168th Street BB217, New York, NY 10032, USA

*To whom correspondence should be addressed. Tel: +1 2123054018; Fax: +1 2123057932; Email: kernytsky{at}cubic.bioc.columbia.edu

Prediction of trans-membrane helices continues to be a difficult task with a few prediction methods clearly taking the lead; none of these is clearly best on all accounts. Recently, we have carefully set up protocols for benchmarking the most relevant aspects of prediction accuracy and have applied it to >30 prediction methods. Here, we present the extension of that analysis to the level of an automatic web server evaluating new methods (http://cubic.bioc.columbia.edu/services/tmh_benchmark/). The most important achievements of the tool are: (i) any new method is compared to the battery of well-established tools; (ii) the battery of measures explored allows spotting strengths in methods that may not be ‘best’ overall. In particular, we report per-residue and per-segment scores for accuracy and the error-rates for confusing membrane helices with globular proteins or signal peptides. An additional feature is that developers can directly investigate any hydrophobicity scale for its potential in predicting membrane helices.


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