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A profile hidden Markov model for signal peptides generated by HMMER
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Abstract
Summary: Although the HMMER package is widely used to produce profile hidden Markov models (profile HMMs) for protein domains, it has been difficult to create a profile HMM for signal peptides. Here we describe an approach for building a complex model of eukaryotic signal peptides by the standard HMMER package. Signal peptide prediction with this model gives a 95.6% sensitivity and 95.7% specificity.
Availability: The profile HMM for signal peptides, data sets, and the scripts for analyzing data are available for non-commercial use at http://share.gene.com/.
Contact: zemin@gene.com
* To whom correspondence should be addressed.
Title: A profile hidden Markov model for signal peptides generated by HMMER
Description:
Abstract
Summary: Although the HMMER package is widely used to produce profile hidden Markov models (profile HMMs) for protein domains, it has been difficult to create a profile HMM for signal peptides.
Here we describe an approach for building a complex model of eukaryotic signal peptides by the standard HMMER package.
Signal peptide prediction with this model gives a 95.
6% sensitivity and 95.
7% specificity.
Availability: The profile HMM for signal peptides, data sets, and the scripts for analyzing data are available for non-commercial use at http://share.
gene.
com/.
Contact: zemin@gene.
com
* To whom correspondence should be addressed.
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