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

NucPred

Fetching Q09773 from www.uniprot.org...

The NucPred score for your sequence is 0.59 (see score help below)

   1  MSLKSFFNFNKKTKLHDIEEDVISEIGSAGSALRTDAHMLKANDVYYKSE    50
  51  TDSHTVLRFMKPSENEKIHPVRHSKYEDKSKLPFETIPDPVLKYVKRARD   100
 101  AELQPQLAKVSQKLFADISTATAAEKLQFTVPRRARFEINDPRNPTFSMM   150
 151  ALQDIISVLEYRRNKNPTSTAHICIDKKGKEAVSYSWDKILNRAKQFASV   200
 201  AQNHVGLKPGTRVILYYRKSEASEYIISIFGCLLLGIVVIPLSPSSSSES   250
 251  LKLVVNEEKVRVAFTTEATYRIFIKDTEVNNAKSLAWWKSNDFTNYKFEQ   300
 301  IKQYRMRANDTVLIDYTFSSSTYNDIKAVYTTKTFLSQMRNLTSSMITNP   350
 351  ARQAGWKLHNFEDSKDVLITNFHPSMPLGLIMGVFNSVFAGYCTIFCDEE   400
 401  VLKTPGLLAYLITKYRCTYSLFDYAGLKQTVYNYQEDPKSTLSFKKNYTP   450
 451  NLSSLKLCMVECEVVDPEFNIIVSDRWLQPLGTNNSKEVITPILCLRKFG   500
 501  GIPISFKDWMISYTNRQKHERQMADTCYQEILVLKSSIEKEKVEIVPFLD   550
 551  IRKYSPNEVLCMSPFWYPIPEASVAVVNEDSKNICKVGEVGEIWVYSDCL   600
 601  PKLKAASVINNPQGEQLTDYENNQENKFEKNNSFMDSGLKGFLHNEKIFV   650
 651  LGNKDEQIRQYRKTMVADKLMEEKYVHYSHYLIKKIMKYVPEIFDGVAFE   700
 701  IEIDKAVYSVLVLESPIIKRSLIRNNRLKGRDLFSELVKITESSFQVTQD   750
 751  IFKLDVLSILIAPYKSLPRSRYMGIQAINTNKCKLAFLSGNLPVSYVRFF   800
 801  MDSALPKSKINLNNSKGIWSKDASKHHREIISLNVKQKMDPYKHQNKVSK   850
 851  ARENLLNHFTILDFLKTKSAKTPTSPAILTFNAIEKTKVELTWAHFELKV   900
 901  ASHVEYMQLSVKAKARSHILLLYYDPLEFLISIHSCFHLGVIPIPFQIRE   950
 951  ISQLIGEIEEFTKIAKAFNVEAILVDHKVLISLKSRDISNHFQQTCIDLN  1000
1001  MKAPKIFETTGIPISKRAKKALNLITPGELNNKGKVALISINKLEDGSII  1050
1051  PTQFSHSSLLAFCHEQKEFVIGNEEKPIIGGIEFSSGMGLLHTALLGVYA  1100
1101  GVPTLLIKQENLCNNGSLLFEAIEQNSLSKVMIPLNICQKSFSTAQGCNS  1150
1151  IVINSTLSSIIVPCYDRPISSRVNSIIEDIARIGLAPNKVKLAYSHPINP  1200
1201  FVCWNADSSMEKMKDYFDANQLRSGLVNVREDVLRNRQPLLYGSGTSTLY  1250
1251  NEICIVHPEEKYICQEGEIGEIWINGKHGSYCENNELNSGCELLVQETLD  1300
1301  KKSYSRTGQLGFIHHLKKKDQNMEKVPVLYTLDFIWNTLELNGLNHSVKD  1350
1351  IEETIELVHPNICTDGCILFQASGSVVILLEVHSQQKFASLIPIIVATAL  1400
1401  AAHEIILDCVAFVPKGTFLRRPTGEKRRADILKQWTGGDLKHMTSYLIRQ  1450
1451  DFLLNEDFVGTELIGTTDSYDYSDENLIINSSQLNLL               1487

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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