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

NucPred

Fetching Q20060 from www.uniprot.org...

The NucPred score for your sequence is 0.99 (see score help below)

   1  MPPKTSAAPPQSDESDSDFDDAPVKKPQKKTTKPVNRHKEGSKDPEEELQ    50
  51  RAVNEKFDGSDGEDDDSDLFSLQLPSRPDFLTKPNRADRLMIRNVEVDNF   100
 101  KSYFGKASIGPFHKSFTSIIGPNGSGKSNLIDSLLFVFGFRASKIRSAKV   150
 151  SNLIHKSAGRNPDKCTVTIHFQRIVDIPGHYEVVKDSEFTISRTAFQNNS   200
 201  SSYAIDGRPATKNEVEARLRRVDIDIEHNRFLILQGEVEQIAMMKPVKTT   250
 251  KSETGMVEYLEDIIGTNRLEPFVKLFQRRVNRLTCDLSQQRIARDHARNS   300
 301  KVAMENPVRAAIEFLMKENEATTIHMKLEQRRRQRYLDKIAPKQAELDKM   350
 351  KEEMKSIAETLDTNKNEYKQSEEAQKVMIEERSKLDKNFDSLSKELSDLG   400
 401  TEETRRKEALKRHQANISKAEAEKEKEVKKRSNLEAAPEKAERKIAKCQE   450
 451  EVEQLLEIEKTANEEADKNLDEFEKRSEAPKEEQKKIQETWAQKSNEFNK   500
 501  VRGEARIAREDFEDLKKLANSGTDKLIELKKRLESSEESYAKEKDELDKL   550
 551  KPEFDSWNDKLKQLSTELPTLRNTARQKNQDLAKTRDRLETLRQQNSSCS   600
 601  SSNKVIQALMKEKEAGRIKSFHGRLGDLGVIDPKYEGAICTNFGARLNYL   650
 651  IVGKEEDAKNVINFLVANKLPRQTVQPLDKIKCDKRDLAPNPTNPLPAPR   700
 701  LIDLIDCDPVLKPAFYDMVRSAIVGDSTQEAQRMHRMPACRGVTVCTLEG   750
 751  SMIHPSGSFTGGGKTVKGLILTDKNKMAKQVTPEDKAAERDLAEKLGKLR   800
 801  DEADELKGQEHEMDGQLIEARRKVAEMSNRLSIVTSSVQSAAPAIETLKK   850
 851  TIANQEKEAAKVKVDAKTLEDKQKIVEELEKKRDELGEEAAKVKARQAEI   900
 901  QSKLDGIFKELVQCHRDEAKESLQKRQKLEKDIAKETANISNSGRNIAKC   950
 951  DENISRHDKDIEKMKKKCEELMEKAIDDEEVKSKKETVERFEKQIKKLQT  1000
1001  KGEEMTKKQSELSAAETKLEGELKKCSEGIKELKESMLADRLKVEDIEKK  1050
1051  LAALKVNRIPRFQFLIESSRPEDLEMQIDDKMPVVDENQSPEEVERQKKH  1100
1101  MACVMSDAAYALEFEMRQKVLENTESYENVDGEDRVPVELLSDEKINEIS  1150
1151  SRDAEEMQMKLKVCEQQVEALKAKVDISSIKAYVDKVKQYNEQVIKLTIA  1200
1201  TEVHRKHNQELQRIKQMRLEEFHSAFEFIGKHLVAVFKMLTDGGDAKLEY  1250
1251  IDKDDPFRQGISFMVRPAKKAWKQIQFLSGGEKTLSSLALIFALHMFRPT  1300
1301  PFYVMDEIDAALDYRNVSIIAQYVRQKTENAQFIIISLRNNMFELANRLV  1350
1351  GIYKVDGCTRNVAIDPLRVCEMAKQITDSLGQATCTLPDEVTQRFNETMS  1400
1401  RQNKEMIAQEKQYPNFPSSNEISKAEKIVNVEGRVRKELIQTTRDVTSRP  1450
1451  QSKATTSGDGTERPASRSASRPESRINQMKYPAPRLVERSSSQNVRSPRK  1500
1501  ARNIEADETTPPSKRSNSASTPKRSPMKPLTPSSKKKEKAIVDDDDDME   1549

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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