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

NucPred

Fetching Q80U72 from www.uniprot.org...

The NucPred score for your sequence is 0.65 (see score help below)

   1  MLKCIPLWRCNRHVESVDKRHCSLQVVPEEIYRYSRSLEELLLDANQLRE    50
  51  LPKPFFRLLNLRKLGLSDNEIQRLPPEVANFMQLVELDVSRNDIPEIPES   100
 101  IKFCKALEIADFSGNPLSRLPDGFTQLRSLAHLALNDVSLQALPGDVGNL   150
 151  ANLVTLELRENLLKSLPASLSFLVKLEQLDLGGNDLEVLPDTLGALPNLR   200
 201  ELWLDRNQLSALPPELGNLRRLVCLDVSENRLEELPVELGGLALLTDLLL   250
 251  SQNLLQRLPEGIGQLKQLSILKVDQNRLCEVTEAIGDCENLSELILTENL   300
 301  LTALPHSLGKLTKLTNLNVDRNHLEVLPPEIGGCVALSVLSLRDNRLAVL   350
 351  PPELAHTAELHVLDVAGNRLRSLPFALTHLNLKALWLAENQAQPMLRFQT   400
 401  EDDAQTGEKVLTCYLLPQQPLPSLEDAGQQSSPSESCSDAPLSRVSVIQF   450
 451  EDTLEGEEDAEEAAAEKRGLQRRATPHPSELKVMKRGIEERRNEAFVCKP   500
 501  DPSPPSPSEEEKRLSAESALSGGSVPSASTASEGEPEILPAEVQGLGQHE   550
 551  AMPAQEEYTEDDYNEPTVHFAEDTLIPREDGESEEGQPEAAWPLPSGRQR   600
 601  LIRKDTPHYKKHFKISKLPQPEAVVALLQGVQTDREGPTAGWHNGPHTPW   650
 651  APRAHEEEEEEEEENRDEEEGEATTEEDDKEEAVASAPSVKGVSFDQANN   700
 701  LLIEPARIEEEELTLTIVRQTGGLGISIAGGKGSTPYKGDDEGIFISRVS   750
 751  EEGPAARAGVRVGDKLLEVNGVALQDAEHHEAVEALRGAGAAVQMRVWRE   800
 801  RMVEPENAVTITPLRPEDDYSPREWRGGGLRLPLLQPETPVSLRQRHAAC   850
 851  LVRSEKGLGFSIAGGKGSTPYRAGDGGIFISRIAEGGAAHRAGTLQVGDR   900
 901  VLSINGVDMTEARHDHAVSLLTAASPTISLLLERETGGTYPPSPPPHSSP   950
 951  TPAATVAATVSTAVPGEPLLPRLSPSLLATALEGPYPVEEICLPRAGGPL  1000
1001  GLSIVGGSDHSSHPFGVQDPGVFISKVLPRGLAARCGLRVGDRILAVNGQ  1050
1051  DVREATHQEAVSALLRPCLELCLLVRRDPPPPGMRELCIQKAPGEKLGIS  1100
1101  IRGGAKGHAGNPCDPTDEGIFISKVSPTGAAGRDGRLRVGLRLLEVNQQS  1150
1151  LLGLTHAEAVQLLRSVGDTLTVLVCDGFDTSTTTALEVSPGVIANPFAAG  1200
1201  LGHRNSLESISSIDRELSPEGPGKEKELASQALPWESESAETTGRNLEPL  1250
1251  KLDYRALAALPSAGSLQRGPSATTGGKTTEAPCSPGSQQTKPGVIQPLAQ  1300
1301  AWPRNSPAPRGRGGPCSPPSPDELPANVKQAYRAFAAVPTVHPPENSATQ  1350
1351  PPTPGPAASPEQLSFRERQKYFELEVRVPQAEGPPKRVSLVGADDLRKMQ  1400
1401  EEEARKLQQKRAQMLREEAVTSGPDMGLASDRESPDDQQEAEQPWAVPSH  1450
1451  AGGSSPSSPPPLGGNAPVRTAKAERRHQERLRMQSPELPAPERALSPAER  1500
1501  RALEAEKRALWRAARMKSLEQDALRAQMVLSKSQEGRGKRGPLERLAEAP  1550
1551  SPAPTPSPTPLEDFGLQTSASPGRLPLSGKKFDYRAFAALPSSRPVYDIQ  1600
1601  SPDFVEELRTLEASPSPGSQEEDGEVALVLLGRPSPGAVGPEDMTLCSSR  1650
1651  RSVRPGRRGLGPVPS                                     1665

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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