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

NucPred

Fetching P23225 from www.uniprot.org...

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

   1  MATLPRAAPPTPAALLPLPRAAPPLLLAGRAAAARRSRLRARGPSAAARR    50
  51  SWVVASAASSSSRAVVGGVARREAPPAPQKPTQQAADLNHILSERGACGV   100
 101  GFVANLKNMSSFDIVRDALMALGCMEHRGGCGADSDSGDGAGLMSAVPWD   150
 151  LFDDWASKQGLALFDRRNTGVGMVFLPQDEKSMEEAKAATEKVFVDEGLE   200
 201  VLGWRPVPFNVSVVGRNAKETMPNIQQIFVKVAKEDNADDIERELYISRK   250
 251  LIERAAKSFSWADELYFCSLSSRTIVYKGMLRSEVLGQFYLDLQNELYKS   300
 301  PFAIYHRRFSTNTSPRWPLAQPMRLLGHNGEINTIQGNLNWMRSRETTLK   350
 351  SPVWRGREHEICPFGDPKASDSANLDSTAELLLRSGRSPAEALMILVPEA   400
 401  YKNHPTLSIKYPEVTDFYDYYKGQMEAWDGPALLLFSDGRTVGATLDRNG   450
 451  LRPARYWRTSDDFVYVASEVGVIPMDESKVVMKGRLGPGMMITVDLQTGQ   500
 501  VLENTEVKKTVASASPYGTWLQECTRLIKPVNFLSSTIMDNETVLRHQQA   550
 551  FGYSSEDVQMVIESMASQGKEPTFCMGDDIPLAVLSQRPHLLYDYFKQRF   600
 601  AQVTNPAIDPLREGLVMSLEVNIGKRGNILEVGPENADQVALSSPVLNEG   650
 651  ELETLLNDSKLKPKVLSTYFDIRKGLDGSLDKTIQALCEEADAAVRSGSQ   700
 701  LLVLSDRSEAPEPTRPAIPILLAVGAIHQHLIQNGLRMSASIVADTAQCF   750
 751  STHHFACLIGYGASAVCPYLALETCRQWRLSNKTLNLMRNGKMPTVTIEQ   800
 801  AQRNFIKAVKSGLLKILSKMGISLLSSYCGAQIFEIYGLGQEVVDLAFCG   850
 851  SVSKIGGLTLDELGRETLSFWVKAFSEDTAKRLENFGFIQSRPGGEYHAN   900
 901  NPEMSKLLHKAIREKRDNAYTVYQQHLASRPVNVLRDLLELKSDRAPIPI   950
 951  GKVESATSIVERFCTGGMSLGAISRETHEAIAIAMNRIGGKSNSGEGGED  1000
1001  PIRWNPLTDVVDGYSPTLPHLKGLQNGDTATSAIKQVASGRFGVTPTFLV  1050
1051  NADQIEIKIAQGAKPGEGGQLPGKKVSAYIARLRNSKPGVPLISPPPHHD  1100
1101  IYSIEDLAQLIYDLHQINPKAKVSVKLVSEAGIGTVASGVSKANADIIQI  1150
1151  SGHDGGTGASPISSIKHAGGPWELGLTETNQTLIQNGLRERVVLRVDGGF  1200
1201  RSGQDVLIAAAMGADEYGFGSVAMIATGCVMARICHTNNCPVGVASQREE  1250
1251  LRARFPGVPGDLVNYFLFVAEEVRAALAQLGYEKLDDIIGRTDLLKPKHI  1300
1301  SLVKTQHIDLGYLLSNAGLPEWSSSQIRSQDVHTNGPVLDETILADPEIA  1350
1351  DAIENEKEVSKAFQIYNVDRAVCGRVAGVIAKKYGDTGFAGQLNITFNGS  1400
1401  AGQSFGCFLTPGMNIRLVGEANDYVGKGMAGGELVVVPVDKTGFVPEDAT  1450
1451  IVGNTCLYGATGGQVFVRGKAGERFAVRNSLCQAVVEGTGDHCCEYMTGG  1500
1501  CVVVLGKAGRNVAAGMTGGLAYILDEDDTLVPKVNKEIVKMQRVNAPAGQ  1550
1551  MQLKGLIEAYVEKTGSEKGIAILREWEAYLPLFWQLVPPSEEDSPEACAE  1600
1601  FERVLAKQATTQLSAK                                    1616

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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