Tag: Signal Peptide

PRED-SIGNAL – Prediction of Signal Peptides in Archaea.

PRED-SIGNAL

:: DESCRIPTION

PRED-SIGNAL is a hidden Markov model method that predicts the presence of the SPs and their cleavage sites and also discriminates such proteins from cytoplasmic and transmembrane ones.

::DEVELOPER

The Biophysics and Bioinformatics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Protein Eng Des Sel. 2009 Jan;22(1):27-35. doi: 10.1093/protein/gzn064. Epub 2008 Nov 6.
Prediction of signal peptides in archaea.
Bagos PG, Tsirigos KD, Plessas SK, Liakopoulos TD, Hamodrakas SJ.

LipoP 1.0a – Prediction of Lipoproteins & Signal Peptides in Gram Negative Bacteria

LipoP 1.0a

:: DESCRIPTION

LipoP produces predictions of lipoproteins and discriminates between lipoprotein signal peptides, other signal peptides and n-terminal membrane helices in Gram-negative bacteria.

::DEVELOPER

DTU Health Tech

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

LipoP

:: MORE INFORMATION

Citation

Methods for the bioinformatic identification of bacterial lipoproteins encoded in the genomes of Gram-positive bacteria
O. Rahman, S. P. Cummings, D. J. Harrington and I. C. Sutcliffe
World Journal of Microbiology and Biotechnology 24(11):2377-2382 (2008)

SignalP 5.0 – Predict Signal Peptides

SignalP 5.0

:: DESCRIPTION

SignalP predicts the presence and location of signal peptide cleavage sites in amino acid sequences from different organisms: Gram-positive prokaryotes, Gram-negative prokaryotes, and eukaryotes. The method incorporates a prediction of cleavage sites and a signal peptide/non-signal peptide prediction based on a combination of several artificial neural networks and hidden Markov models.

::DEVELOPER

DTU Health Tech

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

SignalP

:: MORE INFORMATION

Citation:

Improved prediction of signal peptides: SignalP 3.0.
Jannick Dyrløv Bendtsen, Henrik Nielsen, Gunnar von Heijne and Søren Brunak.
J. Mol. Biol., 340:783-795, 2004.

Phobius /PolyPhobius 1.05 – Combined Transmembrane Topology & Signal Peptide Predictor

Phobius /PolyPhobius 1.05

:: DESCRIPTION

Phobius /PolyPhobius is for prediction of transmembrane topology and signal peptides from the amino acid sequence of a protein.

::DEVELOPER

Sonnhammer Bioinformatics Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

Phobius

:: MORE INFORMATION

Citation:

Phobius is described in:

  • Lukas Käll, Anders Krogh and Erik L. L. Sonnhammer.
    A Combined Transmembrane Topology and Signal Peptide Prediction Method.
    Journal of Molecular Biology, 338(5):1027-1036, May 2004.
    (doi) (PubMed)

PolyPhobius is described in:

  • Lukas Käll, Anders Krogh and Erik Sonnhammer.
    An HMM posterior decoder for sequence feature prediction that includes homology information
    Bioinformatics, 21 (Suppl 1):i251-i257, June 2005.
    (doi) (PubMed)

 

SPEPLip – Predictor of Signal Peptide and Lipoprotein Cleavage Sites in Proteins

SPEPLip

:: DESCRIPTION

SPEPlip is a neural network-based method, trained and tested on a set of experimentally derived signal peptides from eukaryotes and prokaryotes. SPEPlip identifies the presence of sorting signals and predicts their cleavage sites.

::DEVELOPER

Bologna Biocomputing Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Perl
  • C Compiler

:: DOWNLOAD

 SPEPLip

:: MORE INFORMATION

Citation

Bioinformatics. 2003 Dec 12;19(18):2498-9.
SPEPlip: the detection of signal peptide and lipoprotein cleavage sites.
Fariselli P, Finocchiaro G, Casadio R.

Philius – Predict Protein Transmembrane Topology and Signal Peptides

Philius

:: DESCRIPTION

Philius predicts protein transmembrane topology and signal peptides.

::DEVELOPER

Noble Research Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 Philius

:: MORE INFORMATION

Citation:

Transmembrane topology and signal peptide prediction using dynamic Bayesian networks
Sheila M. Reynolds, Lukas K?ll, Michael E. Riffle, Jeff A. Bilmes and William Stafford Noble
PLoS Computational Biology. 4(11):e1000213, 2008.