SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching P56960 from www.uniprot.org...

The NucPred score for your sequence is 0.84 (see score help below)

   1  MAPPSPREHQSAPATSATKPDAEMVLPGFPDADSFVKFALGSVVAVTKAS    50
  51  GGLPQFGDEYDFYRSFPAFQAFCETQGDRLLQCMSRVMQYHGCRSNIKDR   100
 101  SKVTELEDKFDLLVDTNDVILERVGMLLDEASGVNKHQQPVLPAGLQVPK   150
 151  TIVSSWNRKAGEYGKKAKSETFRLLHAKNIVRPQLRFREKIDNSNTPFLP   200
 201  KIFVKPNARKPLPLALSKERRERPQDRPEDLDVPPALADFIHQQRTQQVE   250
 251  QDMFAHPYQYELDHFTPPQSVLQRPKPQLYRAVGETPCHLVSSLDELVEL   300
 301  NEKLLGCQEFAVDLEHHSYRSFLGLTCLMQISTRTEDFIVDTLELRSDMY   350
 351  ILNESLTDPAIVKVFHGADSDIEWLQKDFGLYVVNMFDTHQAARLLNLAR   400
 401  HSLDHLLRLYCGVESNKQYQLADWRIRPLPEEMLSYARDDTHYLLYIYDR   450
 451  MRLELWERGNHQPVQLQVVWQRSRDICLKKFVKPIFTDESYLELYRKQKK   500
 501  HLNSQQLTAFQLLFAWRDKTARREDESYGYVLPNHMMLKIAEELPKEPQG   550
 551  IIACCNPVPPLVRQQINEMHLLIQQAREMPLLKSENAAGVRKSGPLPSAE   600
 601  RLENDLFGPHDCSHAPPDNYQNTSTDGTLPLQKQPSLFTEGKEETSVDAG   650
 651  CLLATAVITLFSEPNTEEGGKTPLTVAQKKAQNIMQSFENPFRMFLPSLE   700
 701  HKAHISQAAKFDPSSKIYEISNRWKLASQVQVQKEPKEATKKKVAEQTAA   750
 751  REEAKEEAAAGVLEQAIPVRQQAALENATKKRERATSDLRTIEQKQEKKR   800
 801  LKSSKKAKDPDPPGKDFSPYDYSQSDFRAFAGDSKSKPSSQFDPNKLAPS   850
 851  GKKGVGAKKCKQSVGNKSMSFAVGKSDRGFRHNWPKR                887

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

What does the NucPred score mean?

You have to decide on a NucPred score threshold. Sequences which score greater than or equal to this threshold are predicted to spend some time in the nucleus. Higher thresholds yield fewer predicted nuclear proteins, but these predictions are more accurate (you can have higher confidence in them). The table below gives more details of the performance of NucPred estimated using the sequences it was trained on (by cross-validation). Another benchmark is available in the Bioinformatics 2007 paper.

NucPred score threshold Specificity Sensitivity
see above fraction of proteins predicted to be nuclear that actually are nuclear fraction of true nuclear proteins that are predicted (coverage)
0.10 0.45 0.88
0.20 0.52 0.83
0.30 0.57 0.77
0.40 0.63 0.69
0.50 0.70 0.62
0.60 0.71 0.53
0.70 0.81 0.44
0.80 0.84 0.32
0.90 0.88 0.21
1.00 1.00 0.02

Sequences which score >= 0.8 with NucPred and which are predicted by PredictNLS to contain an NLS have been shown to be 93% correct with a coverage of 16%. (PredictNLS by itself is 87% correct with 26% coverage on the same data.)

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