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

NucPred

Fetching Q5B4C9 from www.uniprot.org...

The NucPred score for your sequence is 0.82 (see score help below)

   1  MRPFIDDAKRRAERRLSASRQSISARRMFASSFPDRLKVDADDAQMDYTA    50
  51  PPSSNDSRDGMQYMQQSVMSLIAAVGSRTDLRARFDDSSDSEEETRTRPR   100
 101  FLSEKPFDQQITASPRADVTLHVPSAPETRSSSRERGRRHRRSISEHKLF   150
 151  RPFKAGSASQDKKQDASPDPGPSTSDRLSPIPVLPRPRSATPRAAPILSR   200
 201  MVEARALLETENPEENPQTLEEKEQGVSKKSQVSPLSRQLMEMFRFPTPE   250
 251  KVVVEYACSLLQSMLLQGYMYVTEGHICFYAYLPRQSTRVIKSGYIYKRG   300
 301  RKNPKYNRYWFSLKEDVLSYYADPSNLYFPSGQIDLRYGISASLTEPKDK   350
 351  SRESRDFQVTTDHRTYYFRADSSVNAKEWVRALQKVIFRTHNEGESIKVA   400
 401  FPIENILDVEESPMVEFAQTFKIRVVESEETYAIDEHYFTFFDPDSGRRA   450
 451  FDLLKGLISGTPTRSPPGLSPLPDHTAQPRRSRGSQNRWSLTSGSKSQVV   500
 501  STRRQRSASTSILGSGTGNENSPQRQEDSSSSFFNSIDQVTESSAVLQSI   550
 551  TDTTESASQILNRSDVFQSPTIHTWQQRTSGTARSNRRHSDEITRSTTEH   600
 601  GLDGISLARDGPEMQYTNSDSEQESKDASRLYSAVALNEIVKAGTYPLQR   650
 651  AAGLAGYLKSRSKEMSNLLATESMGYIEKVSGMWAGGRRHYGETDGLLPD   700
 701  DRALYPETAEESLRDRERFRAHFALPPTEKLEAAYFAYLHRALPLYGKIY   750
 751  ISQNRLCFRSLLPGTRTKMILPLHDIENVEKEKGFQFGYHGLVVVIRGHE   800
 801  ELFFEFNAADARDDCAVTLHQRLESAKFLVESISLSQQETDESEAAKVEH   850
 851  RMLQEARRNASAEQDLRPGLSESSELHSIFDDPRASIVNFKPAEPLKITC   900
 901  LTIGSRGDVQPYIALCKGLLAEGHKPKIATHAEFEPWVRKHGIDFAPVDG   950
 951  DPAELMRLCVENGMFTYSFLKEATAKFRGWIDDLLSSAWRACQDSDLLIE  1000
1001  SPSAMAGIHIAEALRIPYFRGFTMPWSRTRAYPHAFAVPESRLGGAYNYI  1050
1051  TYVMFENVFWRAIAGQVNRWRMKELGLRATNLDKMQPNKVPFLYNFSPSV  1100
1101  VPPPLDFPDWVRITGYWFLSESSDWTPPRALAEFIQCARQDGKKIVYIGF  1150
1151  GSIVVSDPSALTRTVVESVQKADVRCILSKGWSARLGDPTSTKVEIPLPP  1200
1201  EIHQIQSAPHDWLFSQIDAAAHHGGAGTTGASLRAGVPTIIKPFFGDQFF  1250
1251  FGNRVEDLGVGICMKKLNVSVFSRALWTATHDERMIVRAKQLGERIRSED  1300
1301  GVATAIQAIYRDLEYATTLTRQRSSISSTPFSPTPSTKTSDDQNANDDIA  1350
1351  DIEDWTFIGDESDLEFPRRARERAVSGADNIPERTILGSRSIYADS      1396

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.)

Go back to the NucPred Home Page.