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

NucPred

Fetching O00443 from www.uniprot.org...

The NucPred score for your sequence is 0.95 (see score help below)

   1  MAQISSNSGFKECPSSHPEPTRAKDVDKEEALQMEAEALAKLQKDRQVTD    50
  51  NQRGFELSSSTRKKAQVYNKQDYDLMVFPESDSQKRALDIDVEKLTQAEL   100
 101  EKLLLDDSFETKKTPVLPVTPILSPSFSAQLYFRPTIQRGQWPPGLPGPS   150
 151  TYALPSIYPSTYSKQAAFQNGFNPRMPTFPSTEPIYLSLPGQSPYFSYPL   200
 201  TPATPFHPQGSLPIYRPVVSTDMAKLFDKIASTSEFLKNGKARTDLEITD   250
 251  SKVSNLQVSPKSEDISKFDWLDLDPLSKPKVDNVEVLDHEEEKNVSSLLA   300
 301  KDPWDAVLLEERSTANCHLERKVNGKSLSVATVTRSQSLNIRTTQLAKAQ   350
 351  GHISQKDPNGTSSLPTGSSLLQEVEVQNEEMAAFCRSITKLKTKFPYTNH   400
 401  RTNPGYLLSPVTAQRNICGENASVKVSIDIEGFQLPVTFTCDVSSTVEII   450
 451  IMQALCWVHDDLNQVDVGSYVLKVCGQEEVLQNNHCLGSHEHIQNCRKWD   500
 501  TEIRLQLLTFSAMCQNLARTAEDDETPVDLNKHLYQIEKPCKEAMTRHPV   550
 551  EELLDSYHNQVELALQIENQHRAVDQVIKAVRKICSALDGVETLAITESV   600
 601  KKLKRAVNLPRSKTADVTSLFGGEDTSRSSTRGSLNPENPVQVSINQLTA   650
 651  AIYDLLRLHANSGRSPTDCAQSSKSVKEAWTTTEQLQFTIFAAHGISSNW   700
 701  VSNYEKYYLICSLSHNGKDLFKPIQSKKVGTYKNFFYLIKWDELIIFPIQ   750
 751  ISQLPLESVLHLTLFGILNQSSGSSPDSNKQRKGPEALGKVSLPLFDFKR   800
 801  FLTCGTKLLYLWTSSHTNSVPGTVTKKGYVMERIVLQVDFPSPAFDIIYT   850
 851  TPQVDRSIIQQHNLETLENDIKGKLLDILHKDSSLGLSKEDKAFLWEKRY   900
 901  YCFKHPNCLPKILASAPNWKWVNLAKTYSLLHQWPALYPLIALELLDSKF   950
 951  ADQEVRSLAVTWIEAISDDELTDLLPQFVQALKYEIYLNSSLVQFLLSRA  1000
1001  LGNIQIAHNLYWLLKDALHDVQFSTRYEHVLGALLSVGGKRLREELLKQT  1050
1051  KLVQLLGGVAEKVRQASGSARQVVLQRSMERVQSFFQKNKCRLPLKPSLV  1100
1101  AKELNIKSCSFFSSNAVPLKVTMVNADPMGEEINVMFKVGEDLRQDMLAL  1150
1151  QMIKIMDKIWLKEGLDLRMVIFKCLSTGRDRGMVELVPASDTLRKIQVEY  1200
1201  GVTGSFKDKPLAEWLRKYNPSEEEYEKASENFIYSCAGCCVATYVLGICD  1250
1251  RHNDNIMLRSTGHMFHIDFGKFLGHAQMFGSFKRDRAPFVLTSDMAYVIN  1300
1301  GGEKPTIRFQLFVDLCCQAYNLIRKQTNLFLNLLSLMIPSGLPELTSIQD  1350
1351  LKYVRDALQPQTTDAEATIFFTRLIESSLGSIATKFNFFIHNLAQLRFSG  1400
1401  LPSNDEPILSFSPKTYSFRQDGRIKEVSVFTYHKKYNPDKHYIYVVRILR  1450
1451  EGQIEPSFVFRTFDEFQELHNKLSIIFPLWKLPGFPNRMVLGRTHIKDVA  1500
1501  AKRKIELNSYLQSLMNASTDVAECDLVCTFFHPLLRDEKAEGIARSADAG  1550
1551  SFSPTPGQIGGAVKLSISYRNGTLFIMVMHIKDLVTEDGADPNPYVKTYL  1600
1601  LPDNHKTSKRKTKISRKTRNPTFNEMLVYSGYSKETLRQRELQLSVLSAE  1650
1651  SLRENFFLGGVTLPLKDFNLSKETVKWYQLTAATYL                1686

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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