Evaluating eukaryotic secreted protein prediction
10.1186/1471-2105-6-256
Crossref journal-article
Springer Science and Business Media LLC
BMC Bioinformatics (297)
Abstract

Abstract Background Improvements in protein sequence annotation and an increase in the number of annotated protein databases has fueled development of an increasing number of software tools to predict secreted proteins. Six software programs capable of high throughput and employing a wide range of prediction methods, SignalP 3.0, SignalP 2.0, TargetP 1.01, PrediSi, Phobius, and ProtComp 6.0, are evaluated. Results Prediction accuracies were evaluated using 372 unbiased, eukaryotic, SwissProt protein sequences. TargetP, SignalP 3.0 maximum S-score and SignalP 3.0 D-score were the most accurate single scores (90–91% accurate). The combination of a positive TargetP prediction, SignalP 2.0 maximum Y-score, and SignalP 3.0 maximum S-score increased accuracy by six percent. Conclusion Single predictive scores could be highly accurate, but almost all accuracies were slightly less than those reported by program authors. Predictive accuracy could be substantially improved by combining scores from multiple methods into a single composite prediction.

Bibliography

Klee, E. W., & Ellis, L. B. (2005). Evaluating eukaryotic secreted protein prediction. BMC Bioinformatics, 6(1).

Authors 2
  1. Eric W Klee (first)
  2. Lynda BM Ellis (additional)
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Dates
Type When
Created 19 years, 10 months ago (Oct. 15, 2005, 2:13 p.m.)
Deposited 1 year, 7 months ago (Feb. 1, 2024, 12:46 p.m.)
Indexed 1 year, 1 month ago (July 19, 2024, 9:01 p.m.)
Issued 19 years, 10 months ago (Oct. 14, 2005)
Published 19 years, 10 months ago (Oct. 14, 2005)
Published Online 19 years, 10 months ago (Oct. 14, 2005)
Funders 0

None

@article{Klee_2005, title={Evaluating eukaryotic secreted protein prediction}, volume={6}, ISSN={1471-2105}, url={http://dx.doi.org/10.1186/1471-2105-6-256}, DOI={10.1186/1471-2105-6-256}, number={1}, journal={BMC Bioinformatics}, publisher={Springer Science and Business Media LLC}, author={Klee, Eric W and Ellis, Lynda BM}, year={2005}, month=oct }