Taylor, Paul D, Toseland, Christopher P, Attwood, Teresa K, Flower, Darren R (2006) LIPPRED: A web server for accurate prediction of lipoprotein signal sequences and cleavage sites. Bioinformation, 1 (5). pp. 176-9. ISSN 0973-2063. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:47862)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. |
Abstract
Bacterial lipoproteins have many important functions and represent a class of possible vaccine candidates. The prediction of lipoproteins from sequence is thus an important task for computational vaccinology. Naïve-Bayesian networks were trained to identify SpaseII cleavage sites and their preceding signal sequences using a set of 199 distinct lipoprotein sequences. A comprehensive range of sequence models was used to identify the best model for lipoprotein signal sequences. The best performing sequence model was found to be 10-residues in length, including the conserved cysteine lipid attachment site and the nine residues prior to it. The sensitivity of prediction for LipPred was 0.979, while the specificity was 0.742. Here, we describe LipPred, a web server for lipoprotein prediction; available at the URL: http://www.jenner.ac.uk/LipPred/. LipPred is the most accurate method available for the detection of SpaseIIcleaved lipoprotein signal sequences and the prediction of their cleavage sites.
Item Type: | Article |
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Subjects: | Q Science |
Divisions: | Divisions > Division of Natural Sciences > Biosciences |
Depositing User: | Chris Toseland |
Date Deposited: | 07 Apr 2015 10:54 UTC |
Last Modified: | 16 Nov 2021 10:19 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/47862 (The current URI for this page, for reference purposes) |
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