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

NucPred

Fetching Q8CHG3 from www.uniprot.org...

The NucPred score for your sequence is 0.65 (see score help below)

   1  MEDSAPDAVAAAPSGTPKSKLETLPREDLIKFAKKQMMLLQKAKARCTEL    50
  51  DKEVEELKSKPVDGGTDDIIKVLTERLDALLLEKAETEQQCLCLKKENVK   100
 101  MKQEVEDSVTKLEETHKEFEQSHRNYVKEIESCKNELMAVHSEHSKETAI   150
 151  LQKELEEAVHKQVELREQLKSQSDSEDNVRKLQEEIQNITAAFEEQISCL   200
 201  EKKLEATSDEKQQEIIHLQKVIEDKAQHYQKDINTFQAEILQLRATHKEE   250
 251  VTELMSQIETSAKEHEAEINKLKENRVTQCEASENIPEKYQCESENLNEV   300
 301  ASDASPESQNCSVALQEDPSAEQTVCDKVRQLEDSLKELESQHSILKDEV   350
 351  TYMNNLKLKLEMDAQHIKDEFFHEREDLEFKINELLLAKEEQGYVVEKLK   400
 401  YEREDLNRQLCCAVEQHNKEIQRLQEHHQKEVSELSETFISGSEKEKLAL   450
 451  MFEIQGLKEQCENLQHEKQEVVLNYESLREMMEILQTELGESAGKISQEF   500
 501  ETMKQQQASDVHELQQKLRSAFNEKDALLETVNRLQGENEKLLSQQELVP   550
 551  ELESTIKNLQADNSMYLASLGQKDTMLQELEAKISSLAKEKDDFISKIKT   600
 601  SHEEMDDLHQKWEREQRLSVELREAAGQAAQHNSELRQRVSELTGKLDEL   650
 651  VREKSQNDQSITVQMKTMTEDQEALSSKIKSLYEENNRLHSEKAQLSRDL   700
 701  EALQAQQDFAHKEHVAEFEKKLQLMVEERDDLNKLLENEQVQKSFVKTQL   750
 751  YEYLKQLRASILEENEEEDVVKLIQAVGESLVKVKEEEHNLVFEYDARVL   800
 801  ELENKIKCLQEDSAVQCEELRTLVRDSEQEKILLRKELDAVTSAKEALQL   850
 851  DLLEMKNTNEKASLENQTLSTQVEELSQTLHSRNEVHDEKVLVIEHENLR   900
 901  LLLKQRESELQDVRAELILLKDSLEKSPSVKNDQLSLVKELEEKIESLEK   950
 951  ESKDKDEKISKIKLVAVKAKKELDSNRKEAQTLREELESVRSEKDRLSAS  1000
1001  MKEFLQGAESYKSLLLEYDKQSEQLDVEKERAHNFERHIEDLTKQLRNST  1050
1051  CQYERLTSDNEDLLARIETLQANAKLLEAQILEVQKAKGVVEKELDAEKL  1100
1101  QKEQKIKEHVSTVNELEELQLQFQKEKKQLQKTMQELELVKKDAQQTTLM  1150
1151  NMEIADYERLMKELNQKLTNKNSTIEDLEQEMKIQKEKQETLQEEITSLQ  1200
1201  SSVQHYEEKNTKIKQLLVKTKKELADAKQAETDHLLLQASLKGELEASQQ  1250
1251  QVEVYKIQLAEMTSEKHKIHEHLKTSAEQHQRTLSAYQQRVVALQEESRA  1300
1301  AKAEQAAVTSEFESYKVRVHNVLKQQKNKSVSQVETEGAKQEREHLEMLI  1350
1351  DQLKIKLQDSQNSLQISVSEYQTLQAEHDTLLERHNRMLQETVTKEAELR  1400
1401  EKLCSVQSENTMMKSEHSQTMCQLTSQNEALRTSFRDQVRHLQDEHRKTV  1450
1451  ETLQHQLSKLEAQLFQLKSEPSTRSPASSHQPSKSLRERRTTDLPLLDMH  1500
1501  TVAREEGEGMETTDSESVSSAGTHIQSLEQLLSSPDTKLERLAETSLWHN  1550
1551  EFTKEELAEKLSSTTKSADHLNGLLRETEATNAILMEQIKLLKSEIRRLE  1600
1601  RNQEREKSVANLEYLKNVLLRFIFLKPGSERERLLPVIDTMLQLSPEEKG  1650
1651  KLATVAQGEEESASRSSGWASYLHSWSGLR                      1680

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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