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

NucPred

Fetching Q9H3S7 from www.uniprot.org...

The NucPred score for your sequence is 0.63 (see score help below)

   1  MEAVPRMPMIWLDLKEAGDFHFQPAVKKFVLKNYGENPEAYNEELKKLEL    50
  51  LRQNAVRVPRDFEGCSVLRKYLGQLHYLQSRVPMGSGQEAAVPVTWTEIF   100
 101  SGKSVAHEDIKYEQACILYNLGALHSMLGAMDKRVSEEGMKVSCTHFQCA   150
 151  AGAFAYLREHFPQAYSVDMSRQILTLNVNLMLGQAQECLLEKSMLDNRKS   200
 201  FLVARISAQVVDYYKEACRALENPDTASLLGRIQKDWKKLVQMKIYYFAA   250
 251  VAHLHMGKQAEEQQKFGERVAYFQSALDKLNEAIKLAKGQPDTVQDALRF   300
 301  TMDVIGGKYNSAKKDNDFIYHEAVPALDTLQPVKGAPLVKPLPVNPTDPA   350
 351  VTGPDIFAKLVPMAAHEASSLYSEEKAKLLREMMAKIEDKNEVLDQFMDS   400
 401  MQLDPETVDNLDAYSHIPPQLMEKCAALSVRPDTVRNLVQSMQVLSGVFT   450
 451  DVEASLKDIRDLLEEDELLEQKFQEAVGQAGAISITSKAELAEVRREWAK   500
 501  YMEVHEKASFTNSELHRAMNLHVGNLRLLSGPLDQVRAALPTPALSPEDK   550
 551  AVLQNLKRILAKVQEMRDQRVSLEQQLRELIQKDDITASLVTTDHSEMKK   600
 601  LFEEQLKKYDQLKVYLEQNLAAQDRVLCALTEANVQYAAVRRVLSDLDQK   650
 651  WNSTLQTLVASYEAYEDLMKKSQEGRDFYADLESKVAALLERTQSTCQAR   700
 701  EAARQQLLDRELKKKPPPRPTAPKPLLPRREESEAVEAGDPPEELRSLPP   750
 751  DMVAGPRLPDTFLGSATPLHFPPSPFPSSTGPGPHYLSGPLPPGTYSGPT   800
 801  QLIQPRAPGPHAMPVAPGPALYPAPAYTPELGLVPRSSPQHGVVSSPYVG   850
 851  VGPAPPVAGLPSAPPPQFSGPELAMAVRPATTTVDSIQAPIPSHTAPRPN   900
 901  PTPAPPPPCFPVPPPQPLPTPYTYPAGAKQPIPAQHHFSSGIPAGFPAPR   950
 951  IGPQPQPHPQPHPSQAFGPQPPQQPLPLQHPHLFPPQAPGLLPPQSPYPY  1000
1001  APQPGVLGQPPPPLHTQLYPGPAQDPLPAHSGALPFPSPGPPQPPHPPLA  1050
1051  YGPAPSTRPMGPQAAPLTIRGPSSAGQSTPSPHLVPSPAPSPGPGPVPPR  1100
1101  PPAAEPPPCLRRGAAAADLLSSSPESQHGGTQSPGGGQPLLQPTKVDAAE  1150
1151  GRRPQALRLIERDPYEHPERLRQLQQELEAFRGQLGDVGALDTVWRELQD  1200
1201  AQEHDARGRSIAIARCYSLKNRHQDVMPYDSNRVVLRSGKDDYINASCVE  1250
1251  GLSPYCPPLVATQAPLPGTAADFWLMVHEQKVSVIVMLVSEAEMEKQKVA  1300
1301  RYFPTERGQPMVHGALSLALSSVRSTETHVERVLSLQFRDQSLKRSLVHL  1350
1351  HFPTWPELGLPDSPSNLLRFIQEVHAHYLHQRPLHTPIIVHCSSGVGRTG  1400
1401  AFALLYAAVQEVEAGNGIPELPQLVRRMRQQRKHMLQEKLHLRFCYEAVV  1450
1451  RHVEQVLQRHGVPPPCKPLASASISQKNHLPQDSQDLVLGGDVPISSIQA  1500
1501  TIAKLSIRPPGGLESPVASLPGPAEPPGLPPASLPESTPIPSSSPPPLSS  1550
1551  PLPEAPQPKEEPPVPEAPSSGPPSSSLELLASLTPEAFSLDSSLRGKQRM  1600
1601  SKHNFLQAHNGQGLRATRPSDDPLSLLDPLWTLNKT                1636

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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