Static benchmarking of membrane helix predictions

Andrew Kernytsky, Burkhard Rost

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

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/tmhnchmark/). 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.

Original languageEnglish
Pages (from-to)3642-3644
Number of pages3
JournalNucleic Acids Research
Volume31
Issue number13
DOIs
StatePublished - 1 Jul 2003
Externally publishedYes

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