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

NucPred

Fetching O15360 from www.uniprot.org...

The NucPred score for your sequence is 0.92 (see score help below)

   1  MSDSWVPNSASGQDPGGRRRAWAELLAGRVKREKYNPERAQKLKESAVRL    50
  51  LRSHQDLNALLLEVEGPLCKKLSLSKVIDCDSSEAYANHSSSFIGSALQD   100
 101  QASRLGVPVGILSAGMVASSVGQICTAPAETSHPVLLTVEQRKKLSSLLE   150
 151  FAQYLLAHSMFSRLSFCQELWKIQSSLLLEAVWHLHVQGIVSLQELLESH   200
 201  PDMHAVGSWLFRNLCCLCEQMEASCQHADVARAMLSDFVQMFVLRGFQKN   250
 251  SDLRRTVEPEKMPQVTVDVLQRMLIFALDALAAGVQEESSTHKIVRCWFG   300
 301  VFSGHTLGSVISTDPLKRFFSHTLTQILTHSPVLKASDAVQMQREWSFAR   350
 351  THPLLTSLYRRLFVMLSAEELVGHLQEVLETQEVHWQRVLSFVSALVVCF   400
 401  PEAQQLLEDWVARLMAQAFESCQLDSMVTAFLVVRQAALEGPSAFLSYAD   450
 451  WFKASFGSTRGYHGCSKKALVFLFTFLSELVPFESPRYLQVHILHPPLVP   500
 501  GKYRSLLTDYISLAKTRLADLKVSIENMGLYEDLSSAGDITEPHSQALQD   550
 551  VEKAIMVFEHTGNIPVTVMEASIFRRPYYVSHFLPALLTPRVLPKVPDSR   600
 601  VAFIESLKRADKIPPSLYSTYCQACSAAEEKPEDAALGVRAEPNSAEEPL   650
 651  GQLTAALGELRASMTDPSQRDVISAQVAVISERLRAVLGHNEDDSSVEIS   700
 701  KIQLSINTPRLEPREHMAVDLLLTSFCQNLMAASSVAPPERQGPWAALFV   750
 751  RTMCGRVLPAVLTRLCQLLRHQGPSLSAPHVLGLAALAVHLGESRSALPE   800
 801  VDVGPPAPGAGLPVPALFDSLLTCRTRDSLFFCLKFCTAAISYSLCKFSS   850
 851  QSRDTLCSCLSPGLIKKFQFLMFRLFSEARQPLSEEDVASLSWRPLHLPS   900
 901  ADWQRAALSLWTHRTFREVLKEEDVHLTYQDWLHLELEIQPEADALSDTE   950
 951  RQDFHQWAIHEHFLPESSASGGCDGDLQAACTILVNALMDFHQSSRSYDH  1000
1001  SENSDLVFGGRTGNEDIISRLQEMVADLELQQDLIVPLGHTPSQEHFLFE  1050
1051  IFRRRLQALTSGWSVAASLQRQRELLMYKRILLRLPSSVLCGSSFQAEQP  1100
1101  ITARCEQFFHLVNSEMRNFCSHGGALTQDITAHFFRGLLNACLRSRDPSL  1150
1151  MVDFILAKCQTKCPLILTSALVWWPSLEPVLLCRWRRHCQSPLPRELQKL  1200
1201  QEGRQFASDFLSPEAASPAPNPDWLSAAALHFAIQQVREENIRKQLKKLD  1250
1251  CEREELLVFLFFFSLMGLLSSHLTSNSTTDLPKAFHVCAAILECLEKRKI  1300
1301  SWLALFQLTESDLRLGRLLLRVAPDQHTRLLPFAFYSLLSYFHEDAAIRE  1350
1351  EAFLHVAVDMYLKLVQLFVAGDTSTVSPPAGRSLELKGQGNPVELITKAR  1400
1401  LFLLQLIPRCPKKSFSHVAELLADRGDCDPEVSAALQSRQQAAPDADLSQ  1450
1451  EPHLF                                               1455

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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