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

NucPred

Fetching P39993 from www.uniprot.org...

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

   1  MSDREFVTVDPVTIIIKECINLSTAMRKYSKFTSQSGVAALLGGGSEIFS    50
  51  NQDDYLAHTFNNLNTNKHNDPFLSGFIQLRLMLNKLKNLDNIDSLTILQP   100
 101  FLLIVSTSSISGYITSLALDSLQKFFTLNIINESSQNYIGAHRATVNALT   150
 151  HCRFEGSQQLSDDSVLLKVVFLLRSIVDSPYGDLLSNSIIYDVLQTILSL   200
 201  ACNNRRSEVLRNAAQSTMIAVTVKIFSKLKTIEPVNVNQIYINDESYTND   250
 251  VLKADTIGTNVESKEEGSQEDPIGMKVNNEEAISEDDGIEEEHIHSEKST   300
 301  NGAEQLDIVQKTTRSNSRIQAYADDNYGLPVVRQYLNLLLSLIAPENELK   350
 351  HSYSTRIFGLELIQTALEISGDRLQLYPRLFTLISDPIFKSILFIIQNTT   400
 401  KLSLLQATLQLFTTLVVILGNNLQLQIELTLTRIFSILLDDGTANNSSSE   450
 451  NKNKPSIIKELLIEQISILWTRSPSFFTSTFINFDCNLDRADVSINFLKA   500
 501  LTKLALPESALTTTESVPPICLEGLVSLVDDMFDHMKDIDREEFGRQKNE   550
 551  MEILKKRDRKTEFIECTNAFNEKPKKGIPMLIEKGFIASDSDKDIAEFLF   600
 601  NNNNRMNKKTIGLLLCHPDKVSLLNEYIRLFDFSGLRVDEAIRILLTKFR   650
 651  LPGESQQIERIIEAFSSAYCENQDYDPSKISDNAEDDISTVQPDADSVFI   700
 701  LSYSIIMLNTDLHNPQVKEHMSFEDYSGNLKGCCNHKDFPFWYLDRIYCS   750
 751  IRDKEIVMPEEHHGNEKWFEDAWNNLISSTTVITEIKKDTQSVMDKLTPL   800
 801  ELLNFDRAIFKQVGPSIVSTLFNIYVVASDDHISTRMITSLDKCSYISAF   850
 851  FDFKDLFNDILNSIAKGTTLINSSHDDELSTLAFEYGPMPLVQIKFEDTN   900
 901  TEIPVSTDAVRFGRSFKGQLNTVVFFRIIRRNKDPKIFSKELWLNIVNII   950
 951  LTLYEDLILSPDIFPDLQKRLKLSNLPKPSPEISINKSKESKGLLSTFAS  1000
1001  YLKGDEEPTEEEIKSSKKAMECIKSSNIAASVFGNESNITADLIKTLLDS  1050
1051  AKTEKNADNSRYFEAELLFIIELTIALFLFCKEEKELGKFILQKVFQLSH  1100
1101  TKGLTKRTVRRMLTYKILLISLCADQTEYLSKLINDELLKKGDIFTQKFF  1150
1151  ATNQGKEFLKRLFSLTESEFYRGFLLGNENFWKFLRKVTAMKEQSESIFE  1200
1201  YLNESIKTDSNILTNENFMWVLGLLDEISSMGAVGNHWEIEYKKLTESGH  1250
1251  KIDKENPYKKSIELSLKSIQLTSHLLEDNNDLRKNEIFAIIQALAHQCIN  1300
1301  PCKQISEFAVVTLEQTLINKIEIPTNEMESVEELIEGGLLPLLNSSETQE  1350
1351  DQKILISSILTIISNVYLHYLKLGKTSNETFLKILSIFNKFVEDSDIEKK  1400
1401  LQQLILDKKSIEKGNGSSSHGSAHEQTPESNDVEIEATAPIDDNTDDDNK  1450
1451  PKLSDVEKD                                           1459

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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