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

NucPred

Fetching O15085 from www.uniprot.org...

The NucPred score for your sequence is 0.85 (see score help below)

   1  MSVRLPQSIDRLSSLSSLGDSAPERKSPSHHRQPSDASETTGLVQRCVII    50
  51  QKDQHGFGFTVSGDRIVLVQSVRPGGAAMKAGVKEGDRIIKVNGTMVTNS   100
 101  SHLEVVKLIKSGAYVALTLLGSSPSSMGISGLQQDPSPAGAPRITSVIPS   150
 151  PPPPPPLPPPQRITGPKPLQDPEVQKHATQILRNMLRQEEKELQDILPLY   200
 201  GDTSQRPSEGRLSLDSQEGDSGLDSGTERFPSLSESLMNRNSVLSDPGLD   250
 251  SPRTSPVIMARVAQHHRRQGSDAAVPSTGDQGVDQSPKPLIIGPEEDYDP   300
 301  GYFNNESDIIFQDLEKLKSRPAHLGVFLRYIFSQADPSPLLFYLCAEVYQ   350
 351  QASPKDSRSLGKDIWNIFLEKNAPLRVKIPEMLQAEIDSRLRNSEDARGV   400
 401  LCEAQEAAMPEIQEQIHDYRTKRTLGLGSLYGENDLLDLDGDPLRERQVA   450
 451  EKQLAALGDILSKYEEDRSAPMDFALNTYMSHAGIRLREARPSNTAEKAQ   500
 501  SAPDKDKWLPFFPKTKKSSNSKKEKDALEDKKRNPILKYIGKPKSSSQST   550
 551  FHIPLSPVEVKPGNVRNIIQHFENNQQYDAPEPGTQRLSTGSFPEDLLES   600
 601  DSSRSEIRLGRSESLKGREEMKRSRKAENVPRSRSDVDMDAAAEATRLHQ   650
 651  SASSSTSSLSTRSLENPTPPFTPKMGRRSIESPSLGFCTDTLLPHLLEDD   700
 701  LGQLSDLEPEPDAQNWQHTVGKDVVAGLTQREIDRQEVINELFVTEASHL   750
 751  RTLRVLDLIFYQRMKKENLMPREELARLFPNLPELIEIHNSWCEAMKKLR   800
 801  EEGPIIKEISDLMLARFDGPAREELQQVAAQFCSYQSIALELIKTKQRKE   850
 851  SRFQLFMQEAESHPQCRRLQLRDLIISEMQRLTKYPLLLESIIKHTEGGT   900
 901  SEHEKLCRARDQCREILKYVNEAVKQTENRHRLEGYQKRLDATALERASN   950
 951  PLAAEFKSLDLTTRKMIHEGPLTWRISKDKTLDLHVLLLEDLLVLLQKQD  1000
1001  EKLLLKCHSKTAVGSSDSKQTFSPVLKLNAVLIRSVATDKRAFFIICTSK  1050
1051  LGPPQIYELVALTSSDKNTWMELLEEAVRNATRHPGAAPMPVHPPPPGPR  1100
1101  EPAQQGPTPSRVELDDSDVFHGEPEPEELPGGTGSQQRVQGKHQVLLEDP  1150
1151  EQEGSAEEEELGVLPCPSTSLDGENRGIRTRNPIHLAFPGPLFMEGLADS  1200
1201  ALEDVENLRHLILWSLLPGHTMETQAAQEPEDDLTPTPSVISVTSHPWDP  1250
1251  GSPGQAPPGGEGDNTQLAGLEGERPEQEDMGLCSLEHLPPRTRNSGIWES  1300
1301  PELDRNLAEDASSTEAAGGYKVVRKAEVAGSKVVPALPESGQSEPGPPEV  1350
1351  EGGTKATGNCFYVSMPSGPPDSSTDHSEAPMSPPQPDSLPAGQTEPQPQL  1400
1401  QGGNDDPRRPSRSPPSLALRDVGMIFHTIEQLTLKLNRLKDMELAHRELL  1450
1451  KSLGGESSGGTTPVGSFHTEAARWTDGSLSPPAKEPLASDSRNSHELGPC  1500
1501  PEDGSDAPLEDSTADAAASPGP                              1522

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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