PredGPI: a GPI-anchor predictor. Export

@article{citeulike:3321836, 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. CONCLUSIONS:PredGPI outperforms all the other previously described methods and is able to correctly replicate the results of previously published high-throughput experiments. PredGPI reaches a lower rate of false positive predictions with respect to other available methods and it is therefore a costless, rapid and accurate method for screening whole proteomes.}, author = {Pierleoni, Andrea and Martelli, Pier L. and Casadio, Rita}, citeulike-article-id = {3321836}, citeulike-linkout-0 = {http://dx.doi.org/10.1186/1471-2105-9-392}, doi = {10.1186/1471-2105-9-392}, issn = {1471-2105}, journal = {BMC Bioinformatics}, keywords = {anchor, bioinformatics, gpi, hmm, prediction, svm}, number = {1}, posted-at = {2008-09-23 14:51:26}, priority = {2}, title = {PredGPI: a GPI-anchor predictor.}, url = {http://dx.doi.org/10.1186/1471-2105-9-392}, volume = {9}, year = {2008} }

TY - JOUR ID - citeulike:3321836 L3 - citeulike-article-id:3321836 N2 - 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. CONCLUSIONS:PredGPI outperforms all the other previously described methods and is able to correctly replicate the results of previously published high-throughput experiments. PredGPI reaches a lower rate of false positive predictions with respect to other available methods and it is therefore a costless, rapid and accurate method for screening whole proteomes. IS - 1 JF - BMC Bioinformatics SN - 1471-2105 TI - PredGPI: a GPI-anchor predictor. VL - 9 KW - anchor KW - bioinformatics KW - gpi KW - hmm KW - prediction KW - svm AU - Pierleoni, Andrea AU - Martelli, Pier AU - Casadio, Rita PY - 2008/// UR - http://dx.doi.org/10.1186/1471-2105-9-392 ER -