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

NucPred

Fetching Q85FM9 from www.uniprot.org...

The NucPred score for your sequence is 0.87 (see score help below)

   1  MMDRNELPFCNKTIDRAAMKRLIGKLVVCFGIASTTNILDQVKVLGFQQA    50
  51  TEASISLGIDDLSAVPTRGWLVRDAEKQGYVSEGHYRCGSLHAIEKLRQS   100
 101  IEAWYATSECLKREMSPSFKMIDPLNPVHMMSVSGARGTISQVHQLLGMR   150
 151  GLMADPRGQVIDLPIRRNLREGLSLTEYIISCYGARKGVVDTAVRTSDAG   200
 201  YLTRRLVEVVQHIAVRRRDCETPRSLAFLTSNTGERRRGFLGTMPHQGLV   250
 251  GRVLADHVYWDVRCIATRNQDISDGLASNLMASSQPIHVRSPLTCKSIFW   300
 301  ICQFCYGWSLAHCNLVELGEAVGIIAGQSIGEPGTQLTLRTFHTGGVFTG   350
 351  DIAEYVRIPFNGLIKFDERLLHPTRTRHGHPAWMCRNDLPLFIGNSVGTQ   400
 401  NSLIPAQSLLMIRTGQYVESQQVIAEVRAKEFPPKECIRKPIYPNSRGEI   450
 451  HWSKFVWHVRDSICNIARLVREASHIWILSGSPSKFDGNSFFHKDQDRVR   500
 501  IKPHPIKRIRSHSEGIFEAQASASNCVDRRKGIQEFGTDSKYFSNWSKRP   550
 551  RSNYILSNVWLERAELENSVSLLMERCQKNIKKLDFVSINVQLNNGSDQD   600
 601  HIFATYENFEYQTIVSGIIKYGTVEIKPVNPKRLQLDGGTGNKSSRPWCR   650
 651  VVRKGNFFLIPEEVYLTHEPSSSILVTNNAIVKKGAQITNNIITKSGGLI   700
 701  RMRKRSRDATTIRILPGYIYNPEKQINISKRGNTLLAPGNRISDDIEVKN   750
 751  WIYLQPFTFRRKGKTFVLMTPVSEYNLSSDSLAQVASRFDKPKTQRRAKA   800
 801  KTLSFICCKNGEKIEVINDVPTQLVRLCLIIEWQKYLHETLPRKRNYFSL   850
 851  ISVKISYLFKTFLQVNPMVSPPTQRGVRVDEIFRTSTPLGKPSPPQLDLA   900
 901  NSCCKSAVNCQGIIHLTLEPATSFLILSPFNLSRNNSVTDTRDGGCGGEI   950
 951  GKYFYGSEDGFFCIGENKKKISLSSKCISENYANPNVEEGWIKARRASSN  1000
1001  LGQRKAEEVGLVGTLSPISCSSIPHHLSLGGKNLSTRKGFVDYSIDKSEH  1050
1051  QDFYLIDESKLLLKCPINFYVKKGFLDKPSYLPTRVFSREIMLISLGLLI  1100
1101  SESRYLHRDRTCFQSGQVMAIHQDYSLVRTGKTFLATRGANPHKSSGDIL  1150
1151  EEGDTLITLPYDRLKSGDITQGLPKVEQLLESRSIASISAGIGDLFEKWC  1200
1201  QNITKLIGNPWSHLLGAGRSMEHCQLILIDQIRKVYESQGVRICDKHLEI  1250
1251  IVRQLTSRVVASEDGVTNVFLPGELVELSQAERINRVLKKSIFYEPIVLG  1300
1301  MTRASLSTTSFLAEASFQETTRVLAKAALRGRIDWLKGLKENVVIGDSVP  1350
1351  VGTGSPEIYCQLNINKEKESRLASGGSKKLTKWETGSSLSGYHKKRDFNP  1400
1401  SFFIRKELNRSFTRLHLDMW                                1420

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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