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

NucPred

Fetching P49015 from www.uniprot.org...

The NucPred score for your sequence is 0.23 (see score help below)

   1  MEPSMDVNSVTISVEGMTCISCVRTIEQKIGKENGIHHIKVSLEEKSATI    50
  51  IYDPKLQTPKTLQEAIDDMGFDALLHNANPLPVLTDTLFLTVTASLTLPW   100
 101  DHIQSTLLKTKGVTDIKIFPQKRTLAVTIIPSIVNANQIKELVPELSLET   150
 151  GTLEKRSGACEDHSMAQAGEVVLKIKVEGMTCHSCTSTTEGKIGKLQGVQ   200
 201  RIKVSLDNQEATIVYQPHLISVEEIKKQIEAMGFPAFVKKQPKYLKLGAI   250
 251  DVERLKNTPVKSLEGSQQRPSYPSDSTATFIIEGMHCKSCVSNIESALPT   300
 301  LQYVSSIAVSLENRSAIVKYNASSVTPEMLIKAIEAVSPGQYRVSIANEV   350
 351  ESTSSSPSSSSLQKMPLNVVSQPLTQETVINISGMTCNSCVQSIEGVVSK   400
 401  KPGVKSIHVSLANSFGTVEYDPLLTAPETLREVIVDMGFDAVLPDMSEPL   450
 451  VVIAQPSLETPLLPSTNDQDNMMTAVHSKCYIQVSGMTCASCVANIERNL   500
 501  RREEGIYSVLVALMAGKAEVRYNPAVIQPPVIAEFIRELGFGATVMENAD   550
 551  EGDGILKLVVRGMTCASCVHKIESTLTKHKGIFYCSVALATNKAHIKYDP   600
 601  EIIGPRDIIHTIGSLGFEASLVKKDRSASHLDHKREIKQWRSSFLVSLFF   650
 651  CTPVMGLMMYMMAMEHHFATIHHNQSMSNEEMIKNHSSMFLERQILPGLS   700
 701  IMNLLSLLLCLPVQFFGGWYFYIQAYKALKHKTANMDVLIVLATTIAFAY   750
 751  SLIILLVAMYERAKVNPITSFDTPPMLFVFIALGRWLEHIAKGKTSEALA   800
 801  KLISLQATEATIVTLDSDNILLSEEQVDVELVQRGDIIKVVPGGKFPVDG   850
 851  RVIEGHSMVDESLITGEAMPVAKKPGSTVIAGSINQNGSLLICATHVGAD   900
 901  TTLSQIVKLVEEAQTSKAPIQQFADKLGGYFVPFIVLVSIATLLVWIIIG   950
 951  FQNFTIVETYFPGYSRSISRTETIIRFAFQASITVLCIACPCSLGLATPT  1000
1001  AVMVGTGVGAQNGILIKGGEPLEMAHKVKVVVFDKTGTITHGTPVVNQVK  1050
1051  VLVESNKIPRSKILAIVGTAESNSEHPLGAAVTKYCKQELDTETLGTCTD  1100
1101  FQVVPGCGISCKVTNIEGLLHKSNLKIEENNTKNASLVQIDAINEQSSTS  1150
1151  SSMIIDAPLSNAVDTQQYKVLIGNREWMIRNGLVISNDVDDSMIDHGRKG  1200
1201  RPAVLVTIDDELCGLIAIADTVKPEAELAVHILKSMGLEVVLMTGDNSKT  1250
1251  ARSIASQVGITKVFAEVLPSHKVAKVKQLQEEGKRVAMVGDGINDSPALA  1300
1301  MANVGIAIGTGTDVTIEAADVVFIRNDLLDVVASIDLSRKTVKRIRINFL  1350
1351  FPLIYNLVGIPIAAGVFLPIGLVFQPWMGSAAMAASSVSVVLSSLFLKLY  1400
1401  RKPTYDNYELRTRSHTGQRSPSEISVHVGIDDASRNSPRLGLLDRIVNYS  1450
1451  RASINSLLSDKRSLNSVVNSEPDKHS                          1476

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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