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

NucPred

Fetching Q8BYI9 from www.uniprot.org...

The NucPred score for your sequence is 0.50 (see score help below)

   1  MGIDGETVVLKNMLIGVNLILLGSMLKPSECRLEVTTERAQRQTVEEEGG    50
  51  ASSYNTSSKEQPMVFNHVYNINVPLESLCSSGLEASAEQDMSAEDDTLAE   100
 101  YIGQTSDHESQVTFTHKINLPKKACPCASSSQVLQELLSRIEMLEREVSL   150
 151  LRDQCNTNCCQESAATGQLDYVPHCSGHGNFSFESCGCICNEGWFGKNCS   200
 201  EPYCPLGCSSRGVCVDGQCICDSEYSGDDCSELRCPTDCSSRGLCVDGEC   250
 251  VCEEPYTGEDCRELRCPGDCSGKGQCANGTCLCQEGYAGEDCSQRRCLNA   300
 301  CSGRGHCQEGLCICEEGYQGPDCSAVAPPEDLRVAGISDRSIELEWDGPM   350
 351  AVTEYVISYQPTALGGLQLQQRVPGDWSGVTIMELEPGLTYNISVYAVIS   400
 401  NILSLPITAKVATHLSTPQGLQFKTITETTVEVQWEPFSFSFDGWEISFI   450
 451  PKNNEGGVIAQLPSDVTSFNQTGLKPGEEYIVNVVALKEQARSPPTSASV   500
 501  STVIDGPTQILVRDVSDTVAFVEWTPPRAKVDFILLKYGLVGGEGGKTTF   550
 551  RLQPPLSQYSVQALRPGSRYEVSISAVRGTNESEASSTQFTTEIDAPKNL   600
 601  RVGSRTATSLDLEWDNSEAEAQEYKVVYSTLAGEQYHEVLVPKGIGPTTK   650
 651  TTLTDLVPGTEYGVGISAVMNSKQSIPATMNARTELDSPRDLMVTASSET   700
 701  SISLIWTKASGPIDHYRITFTPSSGISSEVTVPRDRTSYTLTDLEPGAEY   750
 751  IISITAERGRQQSLESTVDAFTGFRPISHLHFSHVTSSSVNITWSDPSPP   800
 801  ADRLILNYSPRDKEEDMLEVLLDATKRHAVLMGLQPATEYIVNLVAVHGT   850
 851  VTSEPIVGSITTGIDPPKNITISNVTKDSLTVSWSSPVAPFDYYRVSYRP   900
 901  TQVGRLDSSVVPNTVTEFAITRLYPATEYEISLNSVRGREESERICTLVH   950
 951  TAMDSPMDLIATNITPTEALLQWKAPMGEVENYVIVLTHFAIAGETILVD  1000
1001  GVSEEFQLVDLLPSTHYTVTMYATSGPLMSGTIATNFSTLLDPPDNLTAS  1050
1051  EVTRQSALISWQPPRAAIENYVLTYKSTDGSRKELIVDAEDTWIRLEGLS  1100
1101  ENTDYTVLLQAAQEATRSSLTSTVFTTGGRVFSHPQDCAQHLMNGDTLSG  1150
1151  VYTIFLNGELSHKLQVYCDMTTDGGGWIVFQRRQNGQTDFFRKWADYRVG  1200
1201  FGNLEDEFWLGLDNIHRITAQGRYELRVDMRDGQEAVFAYYDKFAVEDSR  1250
1251  SLYKIRIGSYNGTAGDSLSYHQGRPFSTEDRDNDVAVTNCAMSYKGAWWY  1300
1301  KNCHRTNLNGKYGESRHSQGINWYHWKGHEFSIPFVEMKMRPYIHRLTAG  1350
1351  RKRRALKF                                            1358

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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