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

NucPred

Fetching P34643 from www.uniprot.org...

The NucPred score for your sequence is 0.74 (see score help below)

   1  MRRYRIDSMKYEQRMNAGASGFDMSDWNNPYNASPPSSRGGDDDASSVNH    50
  51  SRPRRSRLDNDIPQPRRPILIQPARPVSQKSNRQGTGMSNGSRGLNSTFN   100
 101  GYDRTYSRYHQNSSRGPSEGFSGAPSARNASGYASDYANSRAGVGLLPNN   150
 151  HREPVRPRSTAAERYANASSMRNGFVYDSGESDKTSEELEEDEEEEEVRN   200
 201  FYMEGRAQGSRSVTNTLASEVYNSESESYYYGVVKLGSAIVDHVFRTMPP   250
 251  PEKYYKMPPIDRVAYVFYCAVNNKPYNNIDEFHVIFNREFYSYRGYGDSK   300
 301  DLALFKVCKRMQEEFSLKQLEADRLAYEKARQEAAESEKLDFNQHKIEER   350
 351  EEPKLNISQPEEVLSNGPLHYHSCLQFATIGVGGKLVIIKPAGTIDSITG   400
 401  HVLSTSSVHVDDLKTFLHFDEQSGKVIESVQNFKGPLIAGQTPTHSVRLY   450
 451  IQRQIDALRQIRNAGDVKKSEVVDALLVWQLLEIMVQQHGRVTGPDVATL   500
 501  LTNASEELGEKTGISSNGTSESGSKFEAKERFNKYLLGGHINEAVESAIT   550
 551  DGLYADAMTLIRRLHPNDAKKIEEIEARFMNLRSIDDPFATLVAVSSDQP   600
 601  PPILTNSAFDDDNNWKRHAAIVLANLNSQTAMQTIYHLGLLLAKRERNCA   650
 651  ADFCLLVVCILAGYDPFIPVAHDGDETSRKHIGLVHSGSNLLNRVDGLSG   700
 701  TAGFSFTDLHATDIFDYALRLGNNNVDSPLAKSIDYQLARIEYAKKLSSF   750
 751  GGFATDAFRYCTEVARSLWMYVAAFDKNAMFDLCDLAESLQYMAAATPDE   800
 801  SGWITTMRGMLGAAPVQESQQHVPQPQPVENKSISSEAKKWHDEHQAPLE   850
 851  IGSRNDQQHNDKTVEKPIAPGRASLPPPTLVTESSSESTFTDKSDSSVTV   900
 901  AASASRTSTLTSSTLPPPPSLPKTIEKPISTPPPISKNVVPEMTPPAIVK   950
 951  PPMPTLSMPIPPVSTPIMVSPQPIPIPKPVDASIAKSPRSELDDLWDTSP  1000
1001  PSNQTSYPPAPRNIQPSYSPAPNFANPTAPSVPTPPPAVSSAPVLQQATL  1050
1051  GQASIPNAKTTAPPVPQKQPELALNERKASKGWFGSIKEKVIKSIPSANQ  1100
1101  MILPDDSKPSIVWDPVQKRYVGAGVEEEVVAAPPPVMSAPHLMGGGPDSN  1150
1151  KSSTNSLRSARSGVGSRYLQSGMATSQAPAMDTGMPPMMPPTMPMSFSFM  1200
1201  PAPTEDDSSEYVDPFSGEPTAPSESLSKQNND                    1232

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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