articleBMC BioinformaticsSep 23, 2008GOLD OA

PredGPI: a GPI-anchor predictor

University of Bologna

PubMed
Indexed incrossrefdoajpubmed

Abstract

Background

Several eukaryotic proteins associated to the extracellular leaflet of the plasma membrane carry a Glycosylphosphatidylinositol (GPI) anchor, which is linked to the C-terminal residue after a proteolytic cleavage occurring at the so called omega-site. Computational methods were developed to discriminate proteins that undergo this post-translational modification starting from their aminoacidic sequences. However more accurate methods are needed for a reliable annotation of whole proteomes.

Results

Here we present PredGPI, a prediction method that, by coupling a Hidden Markov Model (HMM) and a Support Vector Machine (SVM), is able to efficiently predict both the presence of the GPI-anchor and the position of the omega-site. PredGPI is trained on a non-redundant dataset of experimentally characterized GPI-anchored proteins whose annotation was carefully checked in the literature.

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677
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Authors

3

Topics & keywords

Keywords
  • Computational biology
  • DNA microarray
  • Biology
  • Computer science
  • Data science
  • Bioinformatics
  • Genetics
  • Gene
UN Sustainable Development Goals
  • Reduced inequalities
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