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

NucPred

Fetching P98094 from www.uniprot.org...

The NucPred score for your sequence is 0.53 (see score help below)

   1  VLVIAPAATSSYDDLAVAILMVDQKKITEVHVLLVNPHTGATLDEKKVKL    50
  51  QWDNKFIAFTKLQVTPKEVEKWKEDFVRLMVKWDGGQHMEIDIPLTSRRG   100
 101  LVFAQTDQPIYTPNNDVNIRLFPVTRQLNPILSSLVVDIMNPDGVVVDRI   150
 151  EKNAFEVEKVMELRPFHVPAITSLGDWKIVSWMKDKPQFNYTSGFKVEEY   200
 201  VLPTFDVSITSEQPYLHVYDKAFTIHIKAMHIYGKPVMGRAYVRYGVKHQ   250
 251  SKRTLLSTSSALARFEQGEAMHTLRQKHILEQYPDPKLLLGQSLYVEASV   300
 301  ISSDAGEIENSILDDIPIVASPYSIKSKWTVPFFKPGVPYIYKVLVLNPD   350
 351  GSPASGVPIKVSFSFDSSGNWITQKRKTMDNGIAMQTINTARNSKKLNIK   400
 401  VQTEDERLEQSQQAEASFTIASYSSPSGSFIHLNAHREVKSPGEHIVFDV   450
 451  FIKSAAKDHVLHFNYLMISNGKIHNFLQEGRKGDTTSVSLLLTPELVPQF   500
 501  RLVAFFILPSGELVADSIIIDVKDSCHAKLSLDVAGGKRLFSPRDNVNFD   550
 551  LSGESDSWVAVGVVDKAAYVLDKKNKLTANKVYKAMEASDLGCSVGSGKT   600
 601  GPLVFRDAGLAIMAKEISGMDDVKDPGCPNGHTRRKRELVLEIAIEKAST   650
 651  YPAELRKCCRDAAIESPLRLSCEERTKHIHDEGEGCQETFLECCKHVEEE   700
 701  LLIAMEEEDEDLGRSQGEDFMIQESQVVIRSHFPESFMWEIIKLSRSAEN   750
 751  GKSRITKKMPDSITTWDIQAVEVSQSKGLCVGPSLELTVFKQFFLKVHTP   800
 801  YALKQYEQVELRVVIYNYMNQDVKGEIQVKCGDGICTDAEQNEPLKSRFA   850
 851  VEKNSATSFSFMVVPLSSSDSSVSVLARVFGSDVHDAVEKDLRVMPEGNY   900
 901  EEMSRSWSVQPRRHGGQQVIVVDNETPQNVVPGTEMSAFLSAQGNLVAET   950
 951  IQNTLKGSKISNLLRLPRGCGEQNMMYTSITVMVARYLNRSDQWNKMGDP  1000
1001  QLKKRSFDFITSGFASQLTYRKPDYSYAAWLHRASSTWLTAFVAKVFSQA  1050
1051  RQLVFIPVSEICGSVRWLMRKQDKDGSFLESKPVVHLNMMGQVTGKVVLT  1100
1101  SFVFIALLEARESCINEVEGFTVVVEKAHGYLTSQAMNGLEDFPLAITAY  1150
1151  ALSLWKVSDGAAKVTMHTLKTSGLQTEELIHWGSNKGKAAAVESTAYGLL  1200
1201  AAIQHEEGEIAEKATNWLSQSATFGGYFQSTQDTVMALQALTGFESCQSR  1250
1251  MKKMDLSFKIRAEENGVFDKEFQITNDNAFVQKPFKVPVHGQLTVTASGT  1300
1301  GQGILTFVKKYREKVVIKKDCKGFSLEITTNLDNQVKQRRRQSINPEFNV  1350
1351  YRFIGCFRYLRNQEPGMVVMDISLPTGFEAKKKDLDDMKNLVDNYIVQYE  1400
1401  IRPGRVFLYLDKVNKDEKNCVGFRLNQVFESNLVLPVTATVFEYYEPDFR  1450
1451  CSKSYHPKMEVNPDASCHGNICNCLQRHCVELKGMADEDRNADRNGNACR  1500
1501  AEYVFIIGVTKVTKTASYININAALKTVLKKGMDQAINVGARRSFVIPMH  1550
1551  CGKNLNVSPGDIYLVMGMHNAHWRNSDRTQYVLTSDTWFEKFPLESVCRL  1600
1601  PSPPASCQVSENFKGCSLKG                                1620

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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