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

NucPred

Fetching P10288 from www.uniprot.org...

The NucPred score for your sequence is 0.48 (see score help below)

   1  MCRIAGTPPRILPPLALMLLAALQQAPIKATCEDMLCKMGFPEDVHSAVV    50
51 SRSVHGGQPLLNVRFQSCDENRKIYFGSSEPEDFRVGEDGVVYAERSFQL 100
101 SAEPTEFVVSARDKETQEEWQMKVKLTPEPAFTGASEKDQKKIEDIIFPW 150
151 QQYKDSSHLKRQKRDWVIPPINLPENSRGPFPQELVRIRSDRDKSLSLRY 200
201 SVTGPGADQPPTGIFIINPISGQLSVTKPLDREQIASFHLRAHAVDVNGN 250
251 QVENPIDIVINVIDMNDNRPEFLHQVWNGTVPEGSKPGTYVMTVTAIDAD 300
301 DPNAQNGMLRYRILSQAPSSPSPNMFTINNETGDIITVAAGLDREKVQQY 350
351 TLIIQATDMEGNPTYGLSNTATAVITVTDVNDNPPEFTAMTFYGEVPENR 400
401 VDVIVANLTVTDKDQPHTPAWNARYQMTGGDPTGQFTILTDPNSNDGLVT 450
451 VVKPIDFETNRMFVLTVAAENQVPLAKGIQHPPQSTATVSITVIDVNESP 500
501 YFVPNPKLVRQEEGLLAGSMLTTFTARDPDRYMQQTSLRYSKLSDPANWL 550
551 KIDPVNGQITTTAVLDRESIYVQNNMYNATFLASDNGIPPMSGTGTLQIY 600
601 LLDINDNAPQVNPKEATTCETLQPNAINITAVDPDIDPNAGPFAFELPDS 650
651 PPSIKRNWTIVRISGDHAQLSLRIRFLEAGIYDVPIVITDSGNPHASSTS 700
701 VLKVKVCQCDINGDCTDVDRIVGAGLGTGAIIAILLCIIILLILVLMFVV 750
751 WMKRRDKERQAKQLLIDPEDDVRDNILKYDEEGGGEEDQDYDLSQLQQPD 800
801 TVEPDAIKPVGIRRLDERPIHAEPQYPVRSAAPHPGDIGDFINEGLKAAD 850
851 NDPTAPPYDSLLVFDYEGSGSTAGSLSSLNSSSSGGEQDYDYLNDWGPRF 900
901 KKLADMYGGGDD 912

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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