Abstract
We have developed an automated method for predicting signal peptide sequences and their cleavage sites in eukaryotic and bacterial protein sequences. It is a 2-layer predictor: the 1st-layer prediction engine is to identify a query protein as secretory or non-secretory; if it is secretory, the process will be automatically continued with the 2nd-layer prediction engine to further identify the cleavage site of its signal peptide. The new predictor is called Signal-CF, where C stands for "coupling" and F for "fusion", meaning that Signal-CF is formed by incorporating the subsite coupling effects along a protein sequence and by fusing the results derived from many width-different scaled windows through a voting system. Signal-CF is featured by high success prediction rates with short computational time, and hence is particularly useful for the analysis of large-scale datasets. Signal-CF is freely available as a web-server at http://chou.med.harvard.edu/bioinf/Signal-CF/ or http://202.120.37.186/bioinf/Signal-CF/.
Keywords
SIGNAL (programming language)Window (computing)ChemistryComputer scienceComputational biologyBiological systemCombinatorial chemistryBiology
MeSH Terms
AlgorithmsAmino Acid SequenceAnimalsBacterial ProteinsComputational BiologyDatabasesProteinEukaryotic CellsHumansMembrane ProteinsModelsBiologicalProtein Sorting SignalsProteinsSerine Endopeptidases
Affiliated Institutions
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Publication Info
- Year
- 2007
- Type
- article
- Volume
- 357
- Issue
- 3
- Pages
- 633-640
- Citations
- 281
- Access
- Closed
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Cite This
Kuo‐Chen Chou,
Hong‐Bin Shen
(2007).
Signal-CF: A subsite-coupled and window-fusing approach for predicting signal peptides.
Biochemical and Biophysical Research Communications
, 357
(3)
, 633-640.
https://doi.org/10.1016/j.bbrc.2007.03.162
Identifiers
- DOI
- 10.1016/j.bbrc.2007.03.162
- PMID
- 17434148