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

NucPred

Fetching O15061 from www.uniprot.org...

The NucPred score for your sequence is 0.64 (see score help below)

   1  MLSWRLQTGPEKAELQELNARLYDYVCRVRELERENLLLEEELRGRRGRE    50
  51  GLWAEGQARCAEEARSLRQQLDELSWATALAEGERDALRRELRELQRLDA   100
 101  EERAARGRLDAELGAQQRELQEALGARAALEALLGRLQAERRGLDAAHER   150
 151  DVRELRARAASLTMHFRARATGPAAPPPRLREVHDSYALLVAESWRETVQ   200
 201  LYEDEVRELEEALRRGQESRLQAEEETRLCAQEAEALRREALGLEQLRAR   250
 251  LEDALLRMREEYGIQAEERQRVIDCLEDEKATLTLAMADWLRDYQDLLQV   300
 301  KTGLSLEVATYRALLEGESNPEIVIWAEHVENMPSEFRNKSYHYTDSLLQ   350
 351  RENERNLFSRQKAPLASFNHSSALYSNLSGHRGSQTGTSIGGDARRGFLG   400
 401  SGYSSSATTQQENSYGKAVSSQTNVRTFSPTYGLLRNTEAQVKTFPDRPK   450
 451  AGDTREVPVYIGEDSTIARESYRDRRDKVAAGASESTRSNERTVILGKKT   500
 501  EVKATREQERNRPETIRTKPEEKMFDSKEKASEERNLRWEELTKLDKEAR   550
 551  QRESQQMKEKAKEKDSPKEKSVREREVPISLEVSQDRRAEVSPKGLQTPV   600
 601  KDAGGGTGREAEARELRFRLGTSDATGSLQGDSMTETVAENIVTSILKQF   650
 651  TQSPETEASADSFPDTKVTYVDRKELPGERKTKTEIVVESKLTEDVDVSD   700
 701  EAGLDYLLSKDIKEVGLKGKSAEQMIGDIINLGLKGREGRAKVVNVEIVE   750
 751  EPVSYVSGEKPEEFSVPFKVEEVEDVSPGPWGLVKEEEGYGESDVTFSVN   800
 801  QHRRTKQPQENTTHVEEVTEAGDSEGEQSYFVSTPDEHPGGHDRDDGSVY   850
 851  GQIHIEEESTIRYSWQDEIVQGTRRRTQKDGAVGEKVVKPLDVPAPSLEG   900
 901  DLGSTHWKEQARSGEFHAEPTVIEKEIKIPHEFHTSMKGISSKEPRQQLV   950
 951  EVIGQLEETLPERMREELSALTREGQGGPGSVSVDVKKVQGAGGSSVTLV  1000
1001  AEVNVSQTVDADRLDLEELSKDEASEMEKAVESVVRESLSRQRSPAPGSP  1050
1051  DEEGGAEAPAAGIRFRRWATRELYIPSGESEVAGGASHSSGQRTPQGPVS  1100
1101  ATVEVSSPTGFAQSQVLEDVSQAARHIKLGPSEVWRTERMSYEGPTAEVV  1150
1151  EVSAGGDLSQAASPTGASRSVRHVTLGPGQSPLSREVIFLGPAPACPEAW  1200
1201  GSPEPGPAESSADMDGSGRHSTFGCRQFHAEKEIIFQGPISAAGKVGDYF  1250
1251  ATEESVGTQTSVRQLQLGPKEGFSGQIQFTAPLSDKVELGVIGDSVHMEG  1300
1301  LPGSSTSIRHISIGPQRHQTTQQIVYHGLVPQLGESGDSESTVHGEGSAD  1350
1351  VHQATHSHTSGRQTVMTEKSTFQSVVSESPQEDSAEDTSGAEMTSGVSRS  1400
1401  FRHIRLGPTETETSEHIAIRGPVSRTFVLAGSADSPELGKLADSSRTLRH  1450
1451  IAPGPKETSFTFQMDVSNVEAIRSRTQEAGALGVSDRGSWRDADSRNDQA  1500
1501  VGVSFKASAGEGDQAHREQGKEQAMFDKKVQLQRMVDQRSVISDEKKVAL  1550
1551  LYLDNEEEENDGHWF                                     1565

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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