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

NucPred

Fetching Q8BI06 from www.uniprot.org...

The NucPred score for your sequence is 0.19 (see score help below)

   1  MRASGRHDVSLKIVLATGCLLLANFSGASSAVATECPDQSPELQPWSPGH    50
  51  NRDYQVHIGHGRKLLLTSSATVHSITISGGGKLVIKDHHEHIVLRTRYIL   100
 101  IDDGGELHAGSALCPFEGNFSIVLYGRADENILPDPYYGLKYIGVDKGGT   150
 151  LELHGQKKLSWTFLNKTLHPGGMQEGGYFFERSWGHRGVIVHVIDAKLGT   200
 201  VVHSDRFDTYRSKKESERLVQYLNAVPDGRILSVAVNDEGSRNLDDTARK   250
 251  AMTKLGSKHFLHLGFRHPWSFITVKGNPSSSVEDHIEYHGHKGSAAARVF   300
 301  KLFQTEHGEHFNVSSSSEWVQDVEWTEWFDHDKVPQSKGGEKISDLRAAY   350
 351  PGKICNRPIDIQATTMDGVALSTEVVYKNGQDYRFACYTRGRACRSYRVR   400
 401  FLCGKPVRPKLTVSIDTNVNSTILSLVDNVRSWRPGDTLVVASTDYSMYQ   450
 451  AEEFRVLPCKACTSTQVKVAGKPQYLHIGEEIDGVDMRAEVGLLTRNIVV   500
 501  MGEMEDRCYPYTNHICDFFDFDTFGGHIKFALGFKAAHLEGVELKYMGQQ   550
 551  LVGQYPIHFHLAGDLDEQGGYDPPTYIRDLSIHHTFSRCITVHGSNGLLI   600
 601  KDVVGYNSLGHCFFTEDGPEERNTFDHCLGLLVKSGTLLPSDRDSRMCKV   650
 651  ITEDSYPGYIPKPRQDCNAVSTFWMANPNNNLINCAAAGSEETGFWFIFH   700
 701  HVPTGPSVGMYSPGYSEHIPLGKFYNNRAHSNYRAGMIIDNGVKTTEASA   750
 751  KDKRPFLSIISARYSPHQDADPLKPREPAIIRHFTAYKNQDHGAWLRGGD   800
 801  VWLDSCRFADNGIGLTLASGGTFPYDDGSKQEIKNSLFVGESGNVGTEMM   850
 851  DNRIWGPGGLDHSGRTLPIGQNFPIRGIQFYDGPINIQNCTFRKFAALEG   900
 901  RHTSALAFRLNNAWQSCPHNNVTNIAFEDVPITSRVFFGEPGPWFNQLDM   950
 951  DGDKTSVFHDLDGSVSEYPGSYLTKDDNWLVRHPDCINVPDWRGAICSGR  1000
1001  YAQMYIQAYKSSNLRMKIIKNDFPSHPLYLEGALTRSTHYQQYQPVITLQ  1050
1051  KGYTIHWDQTAPAELAIWLINFNKGDWIRVGLCYPRGTTFSILSDVHNRL  1100
1101  LKQTSKTGTFVRTLQMDKVEQSYPGRSHYYWDEDSGLLFLKLKAQNEREK  1150
1151  FAFCSMKGCERIKIKALLPRNAGISDCTATAYPRFTERAIVDVPMPRKLF  1200
1201  GAQLKTKDHFLEVKMESSRQHFFHLRNDFAYIEVDGRRYPCSEDGIQIVV  1250
1251  IDGSRGHVVSHGSFRNAILQGIPWQLFNYVAAIPDNSIVLMASKGRYITR  1300
1301  GPWTRVLEKLGADKGLKLKEKMAFVGFKGSFRPIWVTLETEDHKAKIFQV  1350
1351  VPIPVVRKKKL                                         1361

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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