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

NucPred

Fetching Q75BB3 from www.uniprot.org...

The NucPred score for your sequence is 0.12 (see score help below)

   1  MCAVLEPSMIRWLSEVDNIVVSSLPSDYIPSGPAGVKAESCEVELPGSFG    50
  51  VIDEEDSYIRLLSAFATLVCRMSGESDVAMYSKANRLLKLAVPPGVAFQQ   100
 101  LRASVTEAVEGTLALPAVDFDELSALEREKKQLDYYPQYFKVGVVTAADK   150
 151  TKLDQFRYHKFELLLRQVTSSRFEMVYDSERFSPDRIGELGEQLVQFLTL   200
 201  VEAKDDADVYAISLVTSGASRVLPDPTTDLGWGQFRGAIHDIFQHHAETR   250
 251  PDRLCVVETGVGQVAARTFTYSAINCASNIVAHYLLARGIRRGDVVMIYS   300
 301  TRGVDLLVSVLGVLKSGAVFSVIDPAYPPARQNVYLGVAKPAGLIVIQAA   350
 351  GQLDEAVEAFIRDNLSLKARLPALALQTDGAILGGTLPDFHLDTLVPFAS   400
 401  LKNTRTDVVVGPDSNPTLSFTSGSEGIPKGVLGRHFSLTYYFDWMAKRFG   450
 451  LSEDDKFTMLSGIAHDPIQRDMFTPIYLGAQLLVPQEDDIGTPGRLATWM   500
 501  ATHGATVTHLTPAMGQVLTADATTPFPSLKRAFFVGDVLTKRDCARLQSL   550
 551  AENVAIVNMYGSTETQRAVSYFEVPSCSSNPSYLDNLKSIIPAGRGMHNV   600
 601  QLLIVNRHDRTKLCGIGEVGEIYVRAGGLSEGYRGLPEINKEKFIDNWFV   650
 651  DAGHWGGLDLSGDEPWRNYWLGVRDRLYRTGDLGRYLPNGDCECCGRADD   700
 701  QVKIRGFRIELGEIDTNISQYPLCRENITLLRKDQNGESTLISYLVPRSD   750
 751  QKALASFISAVPESIATESIAGSLIKYHKLINDIRGFLKKRLAGYAIPTL   800
 801  IMVMERLPLNPNGKIDKNKLQFPEPTELDRASEHFASETLGLSSFSPLEQ   850
 851  EIRKIWLDLLPTRPAITSSDESFFDLGGTSILATRMAIVLRNRLNISLAL   900
 901  STIFRYPTVKELAKEISRVRGTISDDKSSNSGTTEYYADAKHVSEAELAS   950
 951  KYESRLSLLPSGATSAPVYVFLTGVTGFLGCHILADLLNRSRKPYDITVY  1000
1001  AHVRASDESSALQRIKSVCTAYGLWKNAYAPRIKVVLGNLAEKQFGLPKK  1050
1051  AWHDLQEGIDVIIHNAALVHWVYPYSKLREANVLSTVNVLNLAAAGKAKY  1100
1101  FTFVSSTSALDTKHYLELSNAAIESGGSGVPEDDDLMGGSLGLKGGYGQS  1150
1151  KWAAEFIIKRAGERGLRGCILRPGYVTGSPSTGASNADDFLLRFLRGCVQ  1200
1201  LGKIPDIEGTVNMVPVDYVARLATAASFSSSGNTHMMVVNVNAKPRISFR  1250
1251  DYLLALKEYGYQVTSVPYDEWSKALESSSDEENPLYPLLYLVLDDLPKKL  1300
1301  RSPELDTTNAKFVLEEDFARTNIEPIIITSVSLEVVGSYISFLHKLGFLE  1350
1351  EPAKGSRPLPNISLSDEQISLIAAVATARSSTAKP                 1385

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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