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

NucPred

Fetching P16340 from www.uniprot.org...

The NucPred score for your sequence is 0.16 (see score help below)

   1  MSHSVLVIGSGGREHAICWKLSQSTLVKQIYALPGSFGIQQVEKCRNLDA    50
  51  KVLDPKDFEAIAKWSKKNEISLVVVGPEDPLALGLGDVLQKEGIPCFGPG   100
 101  KQGAQIEADKKWAKDFMLRHGIPTARYESFTDTNKAKAFIRSAPYQALVV   150
 151  KAAGLAAGKGVVVAANVDEACQAVDEILGDLKYGQAGATLVVEELLEGEE   200
 201  ISVLAFTDGKSVRAMLPAQDHKRLGNGDTGPNTGGMGAYCPCPLISQPAL   250
 251  ELVQRAVLERAVQGLIKERITYQGVLYAGLMLTRDGPRVLEFNCRFGDPE   300
 301  TQVILPLLETDLFEVMQACCSGQLDRLPLQWRSGVSAVGVVLASAGYPET   350
 351  STKGCLITGLPDVNSPTQLIFHSGLSVNKQKEALTNGGRVLIAIALDASL   400
 401  KEAAAKATKLAGTITFAGTGAQYRTDIAQKAFKIAIATAPGLSYKDSGVD   450
 451  IDAGDALVQRIKPLSRGTQRPGVLGGLGGFGGLFRLKDLSYKEPVIAEAT   500
 501  QGVGAKIQLALQNELYENIGYDLFAMSANDLLELGAEPVAFLDYIACGKL   550
 551  HVPLAAQLVKGMADGCRDAKCALVGGETAEMPSLYAPGQHDMAGYCVGIV   600
 601  EQARVLPRFDLYEPEDLLVGLPSSGLHCAGFNEILTQLAASKVNLKECSP   650
 651  VGGGKHGLSLAQVLGTPTRLYVQQLLPHLQAGNQIKAVAHVTHGLLHDVQ   700
 701  RLLPEGFEVTLDFGAVPVPDVFGWLAGQLQLSAQTLLERHNCGIGMVLVL   750
 751  PQSSLLWRTALPGAKVLGVLNRQAKASGGAPRVKVRNFVEQLQKLAAPFG   800
 801  GLGETQLPEEVKDVPSSGVKATTREECFENAVGRRLTRVPNHYVDPILIL   850
 851  GTDGVGTKLKIAQQTHRNASVGIDLVAMCVNDILCNGAEPFSFSSYYACG   900
 901  KWQAALAAEVNAGVQEGASQANSSFVASHSAALPLLYEPQVYDLAGFALG   950
 951  IAERSGILPRLDEIQPGDVLIGLPSSGVHSNGFSLVHAVLKRAGLGLNDR  1000
1001  APFSEKTLGEELLVPTKIYVKALSALLSRPNHGIKALAHITGGGLSENIP  1050
1051  RVLRKELAVRLDANKYPLPPVFAWLAAAGNISSTELQRTYNCGLGLVLVV  1100
1101  GATEVDGVLRELRYPQRASVVGEVVARKDPKKPQVVVQNFEASLARTQRM  1150
1151  LSQPRKRVAVLISGKGSNLQALIDAIRDSAQGVYAEIVLVISNKAGVLGL  1200
1201  ERAAKAGIPSMVISHKDFPSREVYDVELTRHLKTARVEFICLAGFMRILS  1250
1251  VPFVREWRGRLINIHPSLLPKFPGLHVQKQALEAGETESGCTVHYVDEGV  1300
1301  DTGAIIVQAAVPILPGDDEETLTQRIHYAEHWAFPRALALLASGALRRVS  1350
1351  EVKKEAPKDIKDSQ                                      1364

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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