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

NucPred

Fetching P35574 from www.uniprot.org...

The NucPred score for your sequence is 0.27 (see score help below)

   1  MGNSFDFGVLLILLKYFKSSRSQNGHSKQIRILLLNEMEKLEKTLFRLEQ    50
  51  GFELQFRLGPTLQGKPVTVFTNYPFPGETFNREKFRSLEWENPTEREDDS   100
 101  DKYCKLNLQQSGSFQYYFLQGNEKSGGGYIVVDPILRVGADNHMLHLDCV   150
 151  TLQTFLAKCLGPFDEWESRLRVAKESGYNMIHFTPLQTLGLSRSCYSLAD   200
 201  QLELNPDFSRPHKKYTWSDVGQLVEKLKREWNVLCITDVVYNHTAANSKW   250
 251  IQEHPECAYNLVNSPHLKPAWVLDRALWHFSCDVAEGKYKNRGVPALIEN   300
 301  DHHLNCIRKVIWEDIFPKLHLWEFFQVDVYKAVEKFRGLLTQETWRVIKS   350
 351  DPKQHLKIIQDPEYRRFGCTVDMNIALATFIPHDNGPAAIEECCNWFRKR   400
 401  IEELNSEKHQLMNYHQEQAVNCLLGNVFYERLAGHGPKLGPVTRKYPLVT   450
 451  RYFTFPFEEMPVSTEETMIHLPNKACFFMAHNGWVMGDDPLRNFAEPGSD   500
 501  VYLRRELICWGDSVKLRYGTKPEDCPYLWAHMRKYTEIIATYFQGVRLDN   550
 551  CHSTPLHVAEYMLDAARKLQPNLYVVAELFTGSEDLDNIFVTRLGISSLI   600
 601  REAMSAYNSHEEGRLVYRYGGEPVGSFVQPCLRPLMPAIAHALFMDITHD   650
 651  NECPIVHRSVYDALPSTTIVSMACCASGSTRGYDELVPHQISVVSEERFY   700
 701  TKWNPEALPSNAGEVNFQSGIIAARCAINKLHQELGAKGFIQVYVDQVDE   750
 751  DIVAVTRHSPSIHQSFVAVSRTAFRNPKTSFYSKDVPQMCIPGKIEEVVL   800
 801  EARTIERNISPYRKDENSINGMPNITVEIREHIQLNESRIVKQAGVTTKG   850
 851  PNEYIQEIEFENLSPGSVIIFRVSLDPHAQVAVGILRNHLTQFSAHFKAG   900
 901  SLAVDNSDPILKIPFASIASKLTLAEINQILYRCESEEQEDGGGCYDIPN   950
 951  WSSLKYAGLQGLMSVLAEIRPKNDLGHPFCDNLRSGDWMIDYVSGRLISR  1000
1001  SGTIAEVGKWLQAMFFYLKQIPRYLIPCYFDAILIGAYTTLLDIAWKQMS  1050
1051  SFVQTGSTFVKHLSLGSVQMCGVGKFPSLPLLSPSLTDVPYRLNEITKEK  1100
1101  EQCCVSLAAGLPHFSSGIFRCWGRDTFIALRGLLLITGRYLEARNIILAF  1150
1151  AGTLRHGLIPNLLGEGTYARYNCRDAVWWWLQCIQDYCKMVPNGLDILKC  1200
1201  PVSRMYPTDDSAPLPAGTLDQPLFDVIQEAMQRHMQGIQFRERNAGPQID  1250
1251  RNMKDEGFTVIAGVNEETGFVYGGNRFNCGTWMDKMGESDRARNRGIPAT  1300
1301  PRDGSAVEIVGLCKSTVRWLLELSKKNIFPYHEVRVKRHGKVVTVSYEEW  1350
1351  NRKIQDNFEKRFHVSEDPSASNEEHPNLVHKRGIYKDSYGASSPWCDYQL  1400
1401  RPNFTIAMVVAPELFTAEKAWKALEIAEKKLLGPLGMKTLDPDDMVYCGI  1450
1451  YDNALDNDNYNLAKGFNYHQGPEWLWPVGYFLRAKLYFSKLMDRETNART  1500
1501  IFLVKNVLSRHYVHLERSPWKGLPELTNENGQYCPFSCETQAWSIATILE  1550
1551  TLYDL                                               1555

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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