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SignalP4 4.0.ws0

Prediction of signal peptide and cleavage sites in gram+, gram- and eukaryotic amino acid sequences

WSDL SignalP4/SignalP4_4_0_ws0.wsdl
Schema definitions ../common/ws_common_1_0b.xsd

We recommend that the first time users should load the WSDL file above to SoapUI and investigate the Web Service operations in that environment. SoapUI is a desktop application for inspecting, invoking, developing and functional/load/compliance testing of Web Services over HTTP. It can be downloaded free of charge from

Examples of client side scripts using the service

signalp_python (4.9 KB) Python 3.1/4.0 ws0 Karunakar Bayyapu
Client script in Python (suds) running the SignalP4 Web Service
signalp_perl2 (5.5 KB) Perl 3.1/4.0 ws0 Karunakar Bayyapu
Client script in Perl (XML::Compile) running the SignalP4 Web Service
signalp_php (4.6 KB) PHP 3.1/4.0 ws0 Karunakar Bayyapu
Client script in PHP running the SignalP4 Web Service
signalp_soap_analysis (8.2 KB) 3.1/4.0 ws0 Karunakar Bayyapu
Detailed analysis of SOAP and WSDL versions with supported clients
signalp_csharp (5.6 KB) C# 3.1/4.0 ws0 Karunakar Bayyapu
Client script in C# (mono) running the SignalP4 Web Service
signalp_cpp (7.9 KB) C++ 3.1/4.0 ws0 Karunakar Bayyapu
currently we are unable to workout this client
signalp_java (6.5 KB) Java 3.1/4.0 ws0 Karunakar Bayyapu
Client script in Java (apache) running the SignalP4 Web Service
example (5.1 KB) FASTA 3.1/4.0 ws0
FASTA examples to submit as STDIN
signalp_perl1 (5.6 KB) Perl 3.1/4.0 ws0 Karunakar Bayyapu
Client script in Perl (SOAP::Lite) running the SignalP4 Web Service


# download the required scripts
signalp_python     wget
signalp_php        wget
signalp_perl1      wget
signalp_perl2      wget
signalp_csharp     wget
signalp_java       wget
signalp_cpp	   wget
example            wget
soap_analysis	   wget



    This Web Service implements SignalP v. 4.0. 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:

    SignalP 4.0 - Discrimination between Signal Peptides and Transmembrane Regions
            T N Petersen, S Brunak, G v Heijne and H Nielsen.
    Nature Methods, 8:785-786, 2011. 

    The main differences between v. 3.1 and this version are:
    * Improved discrimination between signal peptides and transmembrane regions.
    * No HMM method - only one prediction. 

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

    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:

    Other users are requested to write to for details.


    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 (optional)
                "euk"      eukaryotes(default)
                "gram-"    Gram-negative prokaryotes
                "gram+"    Gram-positive prokaryotes

            * 'method'   - prediction method (optional)
                "best"     hidden Markov models(default)
                "notm"     neural network only
            * '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,

    3. fetchResult

    Input :  Unique job identifier of a FINISHED job

            * 'annsource'
                'method'     :SignalP (options ...)
                'version'    :4.0 ws0

            * 'ann'           (array of annotations - one element per input sequence)
                'sequence'     (standard sequence object)
                 'id'        :Sequence identifier
                'annrecords'   (array of predicted features for this sequence)
                 'annrecord'   (annotation record)
                 'feature'   :signal
                   'begin'   :1
                   'end'     :End postion of signal
                   'key'     :D-score
                   'value'   :Prediction position of Y-Max score
                   'key'     :cutoff 
                   'value'   :User defined D-cutoff values for SignalP-noTM and SignalP-TM 
           'comment'   :For "signalp-4.0" the answer is "Y" (yes) and "N"(no) 
                 depending on the selected threshold 
                              and used networks of SignalP are either noTM or TM. 


    Questions concerning the scientific aspects of the SignalP method should
    go to Henrik Nielsen,; technical questions concerning
    the Web Service should go to Karunakar Bayyapu, or
    Kristoffer Rapacki,