DTU Health Tech

Department of Health Technology

NetPhosYeast - 1.0

Serine and threonine phosphorylation sites in yeast proteins

The NetPhosYeast 1.0 server predicts serine and threonine phosphorylation sites in yeast proteins. This service is closely related to NetPhos and NetPhosK.


Sequence submission: paste the sequence(s) and/or upload a local file

Paste a single sequence or several sequences in FASTA format into the field below:

Submit a file in FASTA format directly from your local disk:

Generate graphics

At most 2,000 sequences and 200,000 amino acids per submission; each sequence not longer than 6,000 amino acids.

The sequences are kept confidential and will be deleted after processing.


For publication of results, please cite:

NetPhosYeast: Prediction of protein phosphorylation sites in yeast.
Christian Ravnsborg Ingrell, Martin Lee Miller, Ole Nørregaard Jensen and Nikolaj Blom.
Accepted for publication in Bioinformatics, 2007.


1. Specify the input sequences

All the input sequences must be in one-letter amino acid code. The allowed alphabet (not case sensitive) is as follows:

A C D E F G H I K L M N P Q R S T V W Y and X (unknown)

All the other symbols will be converted to X before processing. The sequences can be input in the following two ways:

  • Paste a single sequence (just the amino acids) or a number of sequences in FASTA format into the upper window of the main server page.

  • Select a FASTA file on your local disk, either by typing the file name into the lower window or by browsing the disk.

Both ways can be employed at the same time: all the specified sequences will be processed. However, there may be not more than 2,000 sequences and 200,000 amino acids in total in one submission. The sequences longer than 6,000 amino acids are not allowed.

2. Customize your run

By default the server produces graphical output illustrating the predictions (in GIF). The graphs can be very valuable for locating the "hot" spots in your proteins. The generation of graphics can be disabled by un-checking the button labelled 'Generate graphics'.

3. Submit the job

Click on the "Submit" button. The status of your job (either 'queued' or 'running') will be displayed and constantly updated until it terminates and the server output appears in the browser window.

At any time during the wait you may enter your e-mail address and simply leave the window. Your job will continue; you will be notified by e-mail when it has terminated. The e-mail message will contain the URL under which the results are stored; they will remain on the server for 24 hours for you to collect them.

Output format


For each input sequence the length and the name of the sequence are stated followed by a table with the prediction results. There is a table row for each serine or threonine residue in the sequence; the columns are:

  • sequence name, truncated to 20 characters;

  • residue position in the sequence;

  • residue: serine (S) or threonine (T);

  • score, a number between 0 and 1; when the score is above 0.5 the residue is a predicted phosphorylation site;

  • kinase: the current version of NetPhosYeast does not make kinase specific predictions;

  • answer: either the word "YES" or a dot ("."), reflecting the score.

After the table, the whole sequence is printed alongside a summary of the predicted glycation sites and their positions.

Finally, if the 'Generate graphics' button has been checked, the server displays a figure in GIF showing a plot of the score for each serine or threonine residue against the sequence position of that residue.


The example below shows the output for the UniProt entry P17536 (TPM1_YEAST), tropomyosin 1.
>TPM1_YEAST	199 amino acids
# netphosyeast-1.0a prediction results
# Sequence		   # x   Context     Score   Kinase    Answer
# -------------------------------------------------------------------
# TPM1_YEAST               9 S   REKLSNLKL   0.390   main        . 
# TPM1_YEAST              17 S   LEAESWQEK   0.692   main       YES
# TPM1_YEAST              45 S   NQIKSLTVK   0.460   main        . 
# TPM1_YEAST              47 T   IKSLTVKNQ   0.508   main       YES
# TPM1_YEAST              65 S   EAGLSDSKQ   0.829   main       YES
# TPM1_YEAST              67 S   GLSDSKQTE   0.502   main       YES
# TPM1_YEAST              70 T   DSKQTEQDN   0.383   main        . 
# TPM1_YEAST              83 S   NQIKSLTVK   0.416   main        . 
# TPM1_YEAST              85 T   IKSLTVKNH   0.338   main        . 
# TPM1_YEAST             105 S   ELAESKQLS   0.434   main        . 
# TPM1_YEAST             109 S   SKQLSEDSH   0.750   main       YES
# TPM1_YEAST             112 S   LSEDSHHLQ   0.578   main       YES
# TPM1_YEAST             117 S   HHLQSNNDN   0.152   main        . 
# TPM1_YEAST             123 S   NDNFSKKNQ   0.406   main        . 
# TPM1_YEAST             136 S   DLEESDTKL   0.620   main       YES
# TPM1_YEAST             138 T   EESDTKLKE   0.308   main        . 
# TPM1_YEAST             143 T   KLKETTEKL   0.269   main        . 
# TPM1_YEAST             144 T   LKETTEKLR   0.213   main        . 
# TPM1_YEAST             150 S   KLRESDLKA   0.685   main       YES
# TPM1_YEAST             179 T   NEELTVKYE   0.172   main        . 
# TPM1_YEAST             195 S   EIAASLENL   0.803   main       YES
%1  ................S.............................T...   #     50
%1  ..............S.S.................................   #    100
%1  ........S..S.......................S.............S   #    150
%1  ............................................S....


NetPhosYeast: Prediction of protein phosphorylation sites in yeast.
Christian Ravnsborg Ingrell1, Martin Lee Miller2, Ole Nørregaard Jensen1 and Nikolaj Blom2.
Accepted for publication in Bioinformatics, 2007.

1University of Southern Denmark, Campusvej 55, DK-5230, Odense M, Denmark
2Center for Biological Sequence Analysis, BioCentrum-DTU, The Technical University of Denmark, DK-2800 Lyngby, Denmark


We here present a neural network based method for the prediction of protein phosphorylation sites in yeast - an important model organism for basic research. Existing protein phosphorylation site predictors are primarily based on mammalian data and show reduced sensitivity on yeast phosphorylation sites compared to those in humans, suggesting the need for a yeast-specific phosphorylation site predictor. NetPhosYeast achieves a correlation coefficient close to 0.75 with a sensitivity of 0.84 and specificity of 0.90 and outperforms existing predictors in the identification of phosphorylation sites in yeast.


If you need help regarding technical issues (e.g. errors or missing results) contact Technical Support. Please include the name of the service and version (e.g. NetPhos-4.0) and the options you have selected. If the error occurs after the job has started running, please include the JOB ID (the long code that you see while the job is running).

If you have scientific questions (e.g. how the method works or how to interpret results), contact Correspondence.

Correspondence: Technical Support: