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

NucPred

Fetching Q9P7H8 from www.uniprot.org...

The NucPred score for your sequence is 0.82 (see score help below)

   1  MAENELRLLNNAELKLALAESEDSFQSLVSVFLCPILLKLDSPHESVRNK    50
  51  TISIANHIMTRLNNNAQAILPLEALVSQYVEANQPLRKRFLLAFISIGEK   100
 101  RIPCSENLALLQICLNHVNEYPLVLLTLTIRLLRFSKPTSAITCSNDVIL   150
 151  SLSSFYLIQKDQRIFSDLQFSQKTVDYRLSLLRWIHLSSWPSNWKWLAYF   200
 201  FASADSHSEVARLADEFTRDSGLPDLENLSHVNVLLDIALDKFRIEALHA   250
 251  NFSVSISLRNKAIQHLLKSKIAANTDKAINCIEFILEAPPSMQPRLIQFT   300
 301  RWVVDKADPNFLKPKAAMILEKILSILSSNIIQSDLLRGFLYTTIGLLTK   350
 351  VDNHLITNSLLTNLLTSLQSELPDVRVSIDEALSIIIPYYSNFRFSNELL   400
 401  PVLEPFIFDSPESPAAYCALRFVLVAFPFDYLPARFICLKVQNPFVFHHS   450
 451  FIEEAKKGLNLSQWVQYNSVYSTNEAQEEDKVRAASYPSASEVISFILSD   500
 501  HDLKKFWESNAAEYCLAILEFIERCIYYSADRSLELYDNDKLSSIDALLI   550
 551  QDSKLREMVSEKCISLSNFNVFLEYVFYGTLLMHFEPTYALSRLVSFAPP   600
 601  EVTFSLPELDFLTSVFNFPLALRNTATRILGIILSTKDSTRISEVLSSCF   650
 651  TIISTSNNKNDNFFKAETALLIIGYTISYLAAQTNSAAVDSFILNSGSIK   700
 701  EFFSVLLEYLGSNVLHKKTTSLAIYKELFVYFTRDWITSYGVDFDEILNV   750
 751  LLRFLKEVEDTNVKVECLHVISRMSLSFSDDEMAEKILKAIYVTYHMDSP   800
 801  DILFASAEAMSILAGGHRNVFVKSTCPIFFQKQLDNYKADHYCFTLDFIL   850
 851  TDCVNSPKPLLRRASSLWLFYIVRYCEPQTYTMTRLNDIYHSFLSFLVTQ   900
 901  DDFVQDTASRGLKAMYDVLEGDERKSFTDNLISTIAADRVDEKTKAPLDA   950
 951  DTALFTTNKGTVATYKDICSLASESGNPDLIYSFLSIAGNSSLWQARKGL  1000
1001  ASGISYLGIPEDQKRKTFSFDTSKSSSLLKKLYRFKHDPNPDVAKTMGEI  1050
1051  WDTLVPSDLNLASHRKYLVEDCLEFMGSRSWRDRESSVNTLVSLLSNVPV  1100
1101  TEYLNQLEDIWNMSFRTLDDIKESVREASFPLCKLLARSVIQSLEKTSHN  1150
1151  TSPSGICKGKRIVSVALPFLLKHAYDQAKEVRSLTYSTITELVRTGNSTL  1200
1201  TSFVPAIMQVMLEYLTEYESKAATFLDFHAKNYSIKQENIDNARTSAVQS  1250
1251  SSMMDTLEKCIGLLDESSMQTLYPILNRMIAKPGGVPTKIGSAQVVMLLV  1300
1301  IRRGPLVKQFASKLLQSLKSSCFDRNAAVSDAFASAIGYLLRVCPLEIAS  1350
1351  QTCQEIIDKFYDGNTNEQIISSKLTVYASRYAPDVFLNLGSLFFPFIFFG  1400
1401  KHSSSISINGVLSKAWDELSSAGSSVNLYSEEIILLIQKNLIVTKWDVKR  1450
1451  PAAAALLEFVNTSRLTYRQNDIYVLLNETMKDKSWPGKELLLEAYVKFLI  1500
1501  KYPEFIKSQKMEEVHQVIVREFKRRNIVYKSHAMESVGELLSDENYRELD  1550
1551  LYELSLNECGTFLQKEWFDKDDELNLEEKIALQRNSVYAMFNSSRPGNKN  1600
1601  CNEMLLTYLSNALDENYLHWNVKLAILKNAPHLKKIMSNEEFLLYKDILY  1650
1651  RCYEDNPSPKAKDYAEVIFGENYLSVLRN                       1679

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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