NetNGlyc – Prediction of n-linked glycosylation sites in human proteins

By | September 22, 2011

INTRODUCTION

This Web Service implements NetNGlyc 1.0b. It predicts N-Glycosylation
sites in human proteins using artificial neural networks that examine
the sequence context of Asn-Xaa-Ser/Thr sequons. The method is described
in detail in the following article:

“Prediction of N-glycosylation sites in human proteins”.
R. Gupta, E. Jung and S. Brunak.
In preparation, 2004.

Alongside this Web Service the NetNGlyc method is also implemented as
a traditional interactive WWW server at:

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

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

NetNglyc 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?netNglyc

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: An object of the type ‘sequencedata’ (see the complete definition
in http://www.cbs.dtu.dk/ws/common/ws_common_1_0a.xsd) holding
protein sequences with mandatory unique identifiers. Each
‘sequence’ is a pair of ‘id’ (identifier) and ‘seq’ (sequence
itself). The sequences must be written in 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.

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: An object of the type ‘anndata’ (see the complete definition
in http://www.cbs.dtu.dk/ws/common/ws_common_1_0b.xsd) holding
the predition results. ‘annsource’ states the ‘method’ (in
this case always ‘netNglyc’) and ‘version’ (in this case 3.1b).
The objects of the type ‘annrecord’ hold the predictions for
a given residue in a given sequence, the fields are:

feature – always “N-glyc”;
pos – sequence residue;
score – ‘potential’: N-glycosylation potential;
score – ‘jury’: jury agreement (see below);
comment – prediction result (see below).

The two scores above should be interpreted as follows:

Any potential crossing the default threshold of 0.5, represents
a predicted glycosylated site. The ‘potential’ score is the averaged
output of nine neural networks. For further information, the ‘jury’
agreement column indicates how many of the nine networks support
the prediction. The final result is shown in the comment field; the
following values are possible:

for glycosylated sites:

+ potential>0.5
++ potential>0.5 AND jury agreement (9/9) OR potential>0.75
+++ potential>0.75 AND jury agreement
++++ potential>0.90 AND jury agreement

and non-glycosylated sites:

– potential<0.5
— potential<0.5 AND jury agreement (all nine <0.5)
— potential<0.32 AND jury agreement

See http://www.cbs.dtu.dk/services/NetNGlyc/output.php for detailed
discussion of the prediction results. Please note that this Web
Service only predicts on asparagines in Asn-Pro-Ser/Thr sequons;
the interactive service mentioned above can be asked to predict on
all the asparagines in the input.

CONTACT

Questions concerning the scientific aspects of the NetPhos method should
go to Ramneek Gupta, ramneek@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
NetNGlyc – Prediction of n-linked glycosylation sites in human proteins
Documentation
http://www.cbs.dtu.dk/services/NetNGlyc
Protocol
SOAP
WSDL
Endpoint
http://ws.cbs.dtu.dk/cgi-bin/soap/ws/quasi-1.2.cgi
Topic
Biology
Type
Tags
, , , , ,
Description

INTRODUCTION This Web Service implements NetNGlyc 1.0b. It predicts N-Glycosylation sites in human proteins using artificial neural networks that examine [...]

Further information

INTRODUCTION

This Web Service implements NetNGlyc 1.0b. It predicts N-Glycosylation
sites in human proteins using artificial neural networks that examine
the sequence context of Asn-Xaa-Ser/Thr sequons. The method is described
in detail in the following article:

“Prediction of N-glycosylation sites in human proteins”.
R. Gupta, E. Jung and S. Brunak.
In preparation, 2004.

Alongside this Web Service the NetNGlyc method is also implemented as
a traditional interactive WWW server at:

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

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

NetNglyc 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?netNglyc

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: An object of the type ‘sequencedata’ (see the complete definition
in http://www.cbs.dtu.dk/ws/common/ws_common_1_0a.xsd) holding
protein sequences with mandatory unique identifiers. Each
‘sequence’ is a pair of ‘id’ (identifier) and ‘seq’ (sequence
itself). The sequences must be written in 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.

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: An object of the type ‘anndata’ (see the complete definition
in http://www.cbs.dtu.dk/ws/common/ws_common_1_0b.xsd) holding
the predition results. ‘annsource’ states the ‘method’ (in
this case always ‘netNglyc’) and ‘version’ (in this case 3.1b).
The objects of the type ‘annrecord’ hold the predictions for
a given residue in a given sequence, the fields are:

feature – always “N-glyc”;
pos – sequence residue;
score – ‘potential’: N-glycosylation potential;
score – ‘jury’: jury agreement (see below);
comment – prediction result (see below).

The two scores above should be interpreted as follows:

Any potential crossing the default threshold of 0.5, represents
a predicted glycosylated site. The ‘potential’ score is the averaged
output of nine neural networks. For further information, the ‘jury’
agreement column indicates how many of the nine networks support
the prediction. The final result is shown in the comment field; the
following values are possible:

for glycosylated sites:

+ potential>0.5
++ potential>0.5 AND jury agreement (9/9) OR potential>0.75
+++ potential>0.75 AND jury agreement
++++ potential>0.90 AND jury agreement

and non-glycosylated sites:

– potential<0.5
— potential<0.5 AND jury agreement (all nine <0.5)
— potential<0.32 AND jury agreement

See http://www.cbs.dtu.dk/services/NetNGlyc/output.php for detailed
discussion of the prediction results. Please note that this Web
Service only predicts on asparagines in Asn-Pro-Ser/Thr sequons;
the interactive service mentioned above can be asked to predict on
all the asparagines in the input.

CONTACT

Questions concerning the scientific aspects of the NetPhos method should
go to Ramneek Gupta, ramneek@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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