Prediction of lipoprotein signal peptides in Gram‐negative bacteria
Technical University of Denmark · Stockholm University
Abstract
A method to predict lipoprotein signal peptides in Gram-negative Eubacteria, LipoP, has been developed. The hidden Markov model (HMM) was able to distinguish between lipoproteins (SPaseII-cleaved proteins), SPaseI-cleaved proteins, cytoplasmic proteins, and transmembrane proteins. This predictor was able to predict 96.8% of the lipoproteins correctly with only 0.3% false positives in a set of SPaseI-cleaved, cytoplasmic, and transmembrane proteins. The results obtained were significantly better than those of previously developed methods. Even though Gram-positive lipoprotein signal peptides differ from Gram-negatives, the HMM was able to identify 92.9% of the lipoproteins included in a Gram-positive test set.…
Citation impact
- FWCI
- 9.16
- Percentile
- 100%
- References
- 34
Authors
6Topics & keywords
- Signal peptide
- Hidden Markov model
- Transmembrane protein
- Gram
- Periplasmic space
- Computational biology
- Lipoprotein
- Biology