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

NucPred

Fetching O74415 from www.uniprot.org...

The NucPred score for your sequence is 0.73 (see score help below)

   1  MESGSIDLDKEIDELSRVLLEHPAHVEKVLKTVEFDKSALRYIDAILDHH    50
  51  LKQIYRNLTSNSPLHTLSLLQKMASWNNGLACVRVFQAIDWNSKIFIKML   100
 101  QLPNQIQNSRKGNKRLKITISKKRSSLLLLFITFLRLGTPEIRLEILNSR   150
 151  KLTTPLFKGIYNDEPSVLKELLQCWLTYVLLDHDVSRATKLSYFNEWSLS   200
 201  CLASLYSRDDEIDGISLCNLVHKFFVDACTVPGEGLCFVSNGWHLQKKVD   250
 251  GQSKTIFNRVLQSFVFSLHVHTSTLQRELVLKILKACPDITASFIERNSL   300
 301  TSEPVLSYQWISFVSLLQAILGMGIPFPFYDAETRTVPPTNIIIENILPS   350
 351  SFSKPVVLKALNGNDKFVCFLTVNTLLASFKRLESVLDEIKRSELSEDNK   400
 401  VELVSKISDAILLRLPDSQTFVQLYSSTESDLLKEGLSRILLYFFTYFPE   450
 451  NILKLKIDTSIFLRLDLSPGMLDRPFSRLHVENIIQILRYLPEVKWFDVV   500
 501  RSPFVFLCLMYLQTSHSKLRDAIISTLNDVFSQTIIFCPSLAVPPILTIL   550
 551  ASLQHTSPTQHKAVLEFLNSCINRCISRVFAYLDVCVDCFKKHSVNSQKK   600
 601  TAPEVSPISVTLIEQIPFFLQKRDISDDSKDAVLSWLSDLFSNLVCTGED   650
 651  ANCLFHLLENVNVTAFDSDYTLKPFNQLMSFIESLAVQKLPDYVNQIGSL   700
 701  SQYLLYSTNDELSNSGIQKFGMNLDFLPLYVVIITKRIAIMLQSGDMRVK   750
 751  KFLELIRELVEFSKEETMATSQSPIRTLLSACINLRPFLLQEQYISFNMD   800
 801  FAEFLIDTNASIKGSVVNTCVLDFLYKSFSDKVQENYNLIRIAAKFMLLW   850
 851  TQEEFIGFSKALDSFLSENDDLIYKNLDYVAPLLFECMQFTSTTNANMFS   900
 901  NNSISVLLKAAILKPTKLTHGMFDALNTMKPIISDFTVFEPALHTVENFD   950
 951  LTDCADEQILLLSSFVNFVPLFRKVIWNLLLNNKEALIQKYELLAILCCD  1000
1001  LAKQYVAEQSQYDLERIRSFCSEVVENNLDLVLQKSHLIELLFPLMKLSD  1050
1051  PKIQYYVKVSNALSEKYLPQGVLELLVLLQKRIDIPSSLRVQTIMRIFAI  1100
1101  LTRVLSDSPQIGLSLEKFLTNFEALIKMNVDILRDEIDKSTLNSFLESAI  1150
1151  VHVTSFSNLRLCLTLAFTMTAEQCDSSRFLQMILAHEKNPLAGEDSSDEI  1200
1201  KATMSAIICKLTIIGKNYTLSVLDQILKLFKGRYTLHDSLLCELLAYFET  1250
1251  LDDISVASRYKGWVITDEYDMMLLARKDGSGVLEPKIAANTVNQYPSEWE  1300
1301  KIDLKVFDDLETTEGLLSSYCSNEWNREVYHPLYALGITASLLHSNQQVS  1350
1351  NIQVIVQQNFLGMIVMGLSLFKEEARFACLNFLRNFIPILDEQKFREKHL  1400
1401  IKLVLASIIVNVPSSENRLSTLMANFYAFSLTVMMKPTHPLFVGINRYYL  1450
1451  QRQHVDVTDIPMYYELLYPSTDYTKSVYWLLTLLHAGLQTNQDLKIYLRR  1500
1501  HVFEMICTLYNSCVVNSEIRTLIEKILLKVVALGGGPMLVKYNAIYPMLQ  1550
1551  MVIPSFQETKENTVVSTT                                  1568

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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