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

NucPred

Fetching P23631 from www.uniprot.org...

The NucPred score for your sequence is 0.40 (see score help below)

   1  MISVGEIMERANHSLVRMRREGEDLTLEEKAEICSELELQQKYVDIASNI    50
  51  IGDLSSLPIAGKIAGTIAAAAMTATHVASGRLDIEQTLLGCSDLPFDQIK   100
 101  EVLENRFNEIDRKLDSHSAALEEITKLVEKSISVVEKTRKQMNKRFDEVM   150
 151  KSIQDAKVSPIISKINNFARYFDTEKERIRGLKLNDYILKLEEPNGILLH   200
 201  FKESRTPTDDSLQAPLFSIIEEGYAVPKSIDDELAFKVLYALLYGTQTYV   250
 251  SVMFFLLEQYSFLANHYYEKGYLEKYDEYFNSLNNVFLDFKSSLVGTGTS   300
 301  NNEGLLDRVLQVLMTVKNSEFLGLEKNGVDEMLNEKINLFNKIKEEIEGK   350
 351  QKMTLSETPENFAQISFDKDITTPIGDWRDGREVRYAVQYASETLFSKIS   400
 401  HWSDPVSVREKACPTLRMPVDQTRRNVLVFRKFDSSKPQLVGEITPYLSN   450
 451  FIDIDRDLYNAASNPDSAVGFKEFTKLNYDGANIRATFDHGRTVFHAAAK   500
 501  SGNDKIMFGLTFLAKSTELNQPDKKGYTPIHVAADSGNAGIVNLLIQRGV   550
 551  SINSKTYHFLQTPLHLAAQRGFVTTFQRLMESPEININERDKDGFTPLHY   600
 601  AIRGGERILEAFLNQISIDVNAKSNTGLTPFHLAIIKNDWPVASTLLGSK   650
 651  KVDINAVDENNITALHYAAILGYLETTKQLINLKEINANVVSSPGLLSAL   700
 701  HYAILYKHDDVASFLMRSSNVNVNLKALGGITPLHLAVIQGRKQILSLMF   750
 751  DIGVNIEQKTDEKYTPLHLAAMSKYPELIQILLDQGSNFEAKTNSGATPL   800
 801  HLATFKGKSQAALILLNNEVNWRDTDENGQMPIHGAAMTGLLDVAQAIIS   850
 851  IDATVVDIEDKNSDTPLNLAAQNSHIDVIKYFIDQGADINTRNKKGLAPL   900
 901  LAFSKKGNLDMVKYLFDKNANVYIADNDGMNFFYYAVQNGHLNIVKYAMS   950
 951  EKDKFEWSNTDNNRRDECPNEECAISHFAVCDAVQFDRIEIVKYFVGTLG  1000
1001  NFAICGPLHQAARYGHLDIVKYLVEEEFLSVDGSKTDTPLCYASENGHFT  1050
1051  VVQYLVSNGAKVNHDCGNGMTAIDKAITKNHLQVVQFLAANGVDFRRKNS  1100
1101  RGTTPFLTAVAENALHIAEYLIREKRQDININEQNVDKDTALHLAVYYKN  1150
1151  LQMIKLLIKYGIDVTIRNAYDKTALDIAIDAKFSNIVEYLKTKSGKFRRE  1200
1201  YKSSYGERSLLQTNQISNFIDRKNIEHDHPLFINADNESSELFSKTASNI  1250
1251  DVIGTLLLIDVLIRYFSKQGYISKESDSASDGITQAAALSITEKFEDVLN  1300
1301  SLHNESAKEQVDLAEVHGKVYAALKSGRNSQIHQILCSSLNSISTLKPED  1350
1351  MEKLESVIMNSHSSVSLPEVTDSANEAYGETLHLFGESCLHSDGILTKKL  1400
1401  M                                                   1401

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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