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

NucPred

Fetching Q8CGB3 from www.uniprot.org...

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

   1  MKSLKSRLWKQDAPGPTSPSSPTAVASTQSAEWNKYDDRLMKAAERGDVE    50
  51  KVSSILAKKGVHPGKLDVEGRSAFHVVASKGNLECLNAILTHGIDVATRD   100
 101  SAGRNALHLAAKYGHALCLQKLLQYNCPTEHVDLQGRTALHDAVMADCPS   150
 151  SIQLLCDHGASVNAKDIDGRTPLVLATQMCRPTICQLLIDRGADVNSRDK   200
 201  QNRTALMLGCEYGCRDAVEVLVKNGADLTLLDALGHDSSYYARIGDNLDI   250
 251  LNLLKTASENTNKGRELWRKGPPLQQRNLSHTQDEGSVKSTQREQREPHS   300
 301  FQDLEIENEDLREKLRKIQQEQRILLDKVNGLQLQLNEEVMVADDLESER   350
 351  EKPKSLLAAKEKQHEESLRTIEALKNRFKYFESDHPGPGSYPSNRKEDML   400
 401  HKQGQMYTTEPQCASPGIPPHMHSRSMLRPLELSLPSQTSYSENEILKKE   450
 451  LETLRTYYDSAKQDRLKFQNELAHKVAECKALALECERVKEDSDEQIKQL   500
 501  EDALKDVQKRMYESEGKVKQMQTHFLALKEHLTNEAATGSHRIIEELREQ   550
 551  LKDLKGKYEGASAEVGKLRSQIKQSEMLVGEFKRDEGRLVEENKRLQKEC   600
 601  GTCEVELERRGRRVVELEGQLKELGAKLALSVPTEKFESMKSSLSNDINE   650
 651  KVKRLAEVGRDYESAQGEIRQLKRDLESVRAQHIRPEEHEQLRSRLEQKS   700
 701  GELGKKVSELTLKNQTLQKDVEKLHADNKLLNQQVHSLTVEMKTRYVPLR   750
 751  VSEEMKRSHDVNVEDLNKKLSEATQRYAEKKQEAERLLAENDKLTKNVSR   800
 801  LEAVFVAPEKHEKELMGLKSNIAELKKQLSELNKKCGEGQEKIRALMSEN   850
 851  SSLKKTLSSQYVPAKTHEEVKASLNSTVEKTNRALLEAKKRFDDTSQEVS   900
 901  KLRDENEVLRRNLENVQNQMKADYVSLEEHSRRMSTVSQSLKEAQEANAA   950
 951  ILADHRQGQEEIVSLHAEIKAQKKELDTIQECIKLKYAPLARLEECERKF  1000
1001  KATEKGLKEQLSEQTHKCRQRDEEVKKGKQENERLRADLAALQKELQDRN  1050
1051  ALAEEAREAERALSGKADELSKQLKDLSQKYSDVKSEREKLVEEKAKQAS  1100
1101  EILAAQNLLQKQPVPLEQVEALKKSLNGTIEQLKEELRSKQRCLEREQQT  1150
1151  VSQLQQLLENQKNSSVTLAEHLKLKEALEKEVGIMKASLREKEEESQKKT  1200
1201  KEVSKLQTEVQTTKQALKNLETREVVDMSKYKATKNDLETQISNLNDKLA  1250
1251  SLNRKYDQACEEKVSAKDEKELLHLSIEQEIRDQKERCDKSLTTIMELQQ  1300
1301  RIQESAKQIEAKDNKITELLNDVERLKQALNGLSQLTYSSGSPTKRQSQL  1350
1351  VDTLQQRVRDLQQQLADADRQHQEVIAIYRTHLLSAAQGHMDEDVQAALL  1400
1401  QIIQMRQGLVC                                         1411

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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