SignalP

By | September 22, 2011

INTRODUCTION

This Web Service implements SignalP v. 3.1. It 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. The method
is described in detail in the following article:

Improved prediction of signal peptides: SignalP 3.0.
J D Bendtsen, H Nielsen, G v Heijne and S Brunak.
J. Mol. Biol., 340:783-795, 2004.

The difference between v. 3.0 and this version is only technical; the
predictions are the same.

Alongside this Web Service the SignalP method is also implemented as
a traditional click-and-paste WWW server at:

http://www.cbs.dtu.dk/services/SignalP/

The traditional server offers more detailed output (graphics), extended
functionality and comprehensive documentation. It is suitable for close
investigation of few proteins; this service is recommended for high
throughput projects.

SignalP is also available as a stand-alone software package to install
and run at the user’s site, with the same functionality. For academic
users there is a download page at:

http://www.cbs.dtu.dk/cgi-bin/nph-sw_request?signalp

Other users are requested to write to software@cbs.dtu.dk for details.

WEB SERVICE OPERATION

This Web Service is fully asynchronous; the usage is split into the
following three operations:

1. runService

Input: The following parameters and data:

* ‘organism’ – organism type of the input sequences (mandatory)
“euk” eukaryotes
“gram-” Gram-negative prokaryotes
“gram+” Gram-positive prokaryotes

* ‘method’ – prediction method (optional)
“nn” neural network only
“hmm” hidden Markov models only
“nn+hmm” both methods (default)

* ‘thnn’ – threshold for yes/no decision by neural nets (optional)
The threshhold setting affects the ‘comment’ field in the
output (see below): if the neural net score is higher than
the selected threshold the comment will be “Y”, else “N”.
The default thresholds are 0.43 for “euk”, 0.45 for “gram+”
and 0.44 for “gram-”; the defaults have been shown to give
the highest correlation coefficient on test data.
Note: ‘thnn’ does not affect the signalp-hmm prediction output.

* ‘sequencedata’ [containing multiple 'sequence' element]
* ‘sequence’
* ‘id’ Unique identifier for the sequence
* ‘comment’ Optional comment
* ‘seq’ Protein sequences, with unique identifiers (mandatory)
The sequences must be written using the one letter amino acid
code: `acdefghiklmnpqrstvwy’ or `ACDEFGHIKLMNPQRSTVWY’. Other
letters will be converted to `X’ and treated as unknown amino
acids. Other symbols, such as whitespace and numbers, will be
ignored. All the input sequences are truncated to 70 aa from
the N-terminal. Currently, at most 2,000 sequences are allowed
per submission.

Output: Unique job identifier

2. pollQueue

Input: Unique job identifier

Output: ‘jobstatus’ – the status of the job
Possible values are QUEUED, ACTIVE, FINISHED, WAITING,
REJECTED, UNKNOWN JOBID or QUEUE DOWN

3. fetchResult

Input : Unique job identifier of a FINISHED job

Output:
* ‘annsource’
‘method’ : SignalP (options …)
‘version’ : 3.1 ws0

* ‘ann’ (array of annotations – one element per input sequence)
‘sequence’ (standard sequence object)
‘id’ : Sequence identifier
‘comment’ : Sequence comment
‘seq’ : Sequence
‘annrecords’ (array of predicted features for this sequence)
‘annrecord’ (annotation record)
‘feature : either ‘signal-nn’ or ‘signal-hmm’
‘range’
‘begin’ : 1
‘end’ : End postion of signal
‘score’
‘key’ : Either nn_score or hmm_score
‘value : Prediction score:
For “signalp-3.1-nn” D score, for “signalp-3.1-hmm”
the signal peptide branch probability (see the
article)
‘comment : Answer: For “signalp-3.1-nn” the answer is “Y” (yes) and “N”
(no) depending on the selected threshold.
For “signalp-3.1-hmm” the answer is “S” f or signal
peptide, “A” for signal anchor (“euk” only) and “Q”
for none of the above.

KNOWN BUGS

2007-01-30 Error handling: some error messages may be non-informative;
fix in progress;

2007-01-29 The server side may time out processing large submission;
temporary fix: submit not more than 2,000 sequences at a
time; permanent fix in progress.

CONTACT

Questions concerning the scientific aspects of the SignalP method should
go to Henrik Nielsen, hnielsen@cbs.dtu.dk; technical questions concerning
the Web Service should go to Peter Fischer Hallin, pfh@cbs.dtu.dk or
Kristoffer Rapacki, rapacki@cbs.dtu.dk.

Name
SignalP
Documentation
http://www.cbs.dtu.dk/ws/ws.php?entry=SignalP
Protocol
SOAP
WSDL
Endpoint
http://ws.cbs.dtu.dk/cgi-bin/soap/ws/quasi.cgi?log
Topic
Biology
Type
Tags
, , , , , , , ,
Description

INTRODUCTION This Web Service implements SignalP v. 3.1. It predicts the presence and location of signal peptide cleavage sites in [...]

Further information

INTRODUCTION

This Web Service implements SignalP v. 3.1. It 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. The method
is described in detail in the following article:

Improved prediction of signal peptides: SignalP 3.0.
J D Bendtsen, H Nielsen, G v Heijne and S Brunak.
J. Mol. Biol., 340:783-795, 2004.

The difference between v. 3.0 and this version is only technical; the
predictions are the same.

Alongside this Web Service the SignalP method is also implemented as
a traditional click-and-paste WWW server at:

http://www.cbs.dtu.dk/services/SignalP/

The traditional server offers more detailed output (graphics), extended
functionality and comprehensive documentation. It is suitable for close
investigation of few proteins; this service is recommended for high
throughput projects.

SignalP is also available as a stand-alone software package to install
and run at the user’s site, with the same functionality. For academic
users there is a download page at:

http://www.cbs.dtu.dk/cgi-bin/nph-sw_request?signalp

Other users are requested to write to software@cbs.dtu.dk for details.

WEB SERVICE OPERATION

This Web Service is fully asynchronous; the usage is split into the
following three operations:

1. runService

Input: The following parameters and data:

* ‘organism’ – organism type of the input sequences (mandatory)
“euk” eukaryotes
“gram-” Gram-negative prokaryotes
“gram+” Gram-positive prokaryotes

* ‘method’ – prediction method (optional)
“nn” neural network only
“hmm” hidden Markov models only
“nn+hmm” both methods (default)

* ‘thnn’ – threshold for yes/no decision by neural nets (optional)
The threshhold setting affects the ‘comment’ field in the
output (see below): if the neural net score is higher than
the selected threshold the comment will be “Y”, else “N”.
The default thresholds are 0.43 for “euk”, 0.45 for “gram+”
and 0.44 for “gram-”; the defaults have been shown to give
the highest correlation coefficient on test data.
Note: ‘thnn’ does not affect the signalp-hmm prediction output.

* ‘sequencedata’ [containing multiple 'sequence' element]
* ‘sequence’
* ‘id’ Unique identifier for the sequence
* ‘comment’ Optional comment
* ‘seq’ Protein sequences, with unique identifiers (mandatory)
The sequences must be written using the one letter amino acid
code: `acdefghiklmnpqrstvwy’ or `ACDEFGHIKLMNPQRSTVWY’. Other
letters will be converted to `X’ and treated as unknown amino
acids. Other symbols, such as whitespace and numbers, will be
ignored. All the input sequences are truncated to 70 aa from
the N-terminal. Currently, at most 2,000 sequences are allowed
per submission.

Output: Unique job identifier

2. pollQueue

Input: Unique job identifier

Output: ‘jobstatus’ – the status of the job
Possible values are QUEUED, ACTIVE, FINISHED, WAITING,
REJECTED, UNKNOWN JOBID or QUEUE DOWN

3. fetchResult

Input : Unique job identifier of a FINISHED job

Output:
* ‘annsource’
‘method’ : SignalP (options …)
‘version’ : 3.1 ws0

* ‘ann’ (array of annotations – one element per input sequence)
‘sequence’ (standard sequence object)
‘id’ : Sequence identifier
‘comment’ : Sequence comment
‘seq’ : Sequence
‘annrecords’ (array of predicted features for this sequence)
‘annrecord’ (annotation record)
‘feature : either ‘signal-nn’ or ‘signal-hmm’
‘range’
‘begin’ : 1
‘end’ : End postion of signal
‘score’
‘key’ : Either nn_score or hmm_score
‘value : Prediction score:
For “signalp-3.1-nn” D score, for “signalp-3.1-hmm”
the signal peptide branch probability (see the
article)
‘comment : Answer: For “signalp-3.1-nn” the answer is “Y” (yes) and “N”
(no) depending on the selected threshold.
For “signalp-3.1-hmm” the answer is “S” f or signal
peptide, “A” for signal anchor (“euk” only) and “Q”
for none of the above.

KNOWN BUGS

2007-01-30 Error handling: some error messages may be non-informative;
fix in progress;

2007-01-29 The server side may time out processing large submission;
temporary fix: submit not more than 2,000 sequences at a
time; permanent fix in progress.

CONTACT

Questions concerning the scientific aspects of the SignalP method should
go to Henrik Nielsen, hnielsen@cbs.dtu.dk; technical questions concerning
the Web Service should go to Peter Fischer Hallin, pfh@cbs.dtu.dk or
Kristoffer Rapacki, rapacki@cbs.dtu.dk.

Original source
BioCatalogue

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