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

NucPred

Fetching Q9R016 from www.uniprot.org...

The NucPred score for your sequence is 0.60 (see score help below)

   1  MAEHGESSEDRISEIDYEFLPELSALLGVDAFQVAKSQEEEEHKERMKMK    50
  51  KGFNSQMRSEAKRLKTFETYDTFRSWTPQEMAAAGFYHTGVRLGVQCFCC   100
 101  SLILFGNSLRKLPIERHKKLRPECEFLQGKDVGNIGKYDIRVKRPEKMLR   150
 151  GGKARYHEEEARLESFEDWPFYAHGTSPRVLSAAGFVFTGKRDTVQCFSC   200
 201  GGSLGNWEEGDDPWKEHAKWFPKCEFLQSKKSSEEIAQYIQSYEGFVHVT   250
 251  GEHFVKSWVRRELPMVSAYCNDSVFANEELRMDMFKDWPQESPVGVEALV   300
 301  RAGFFYTGKKDIVRCFSCGGCLEKWAEGDDPMEDHIKFFPECVFLQTLKS   350
 351  SAEVIPTLQSQYALPEATETTRESNHGDAAAVHSTVVDLGRSEAQWFQEA   400
 401  RSLSEQLRDNYTKATFRHMNLPEVCSSLGTDHLLSCDVSIISKHISQPVQ   450
 451  EALTIPEVFSNLNSVMCVEGETGSGKTTFLKRIAFLWASGCCPLLYRFQL   500
 501  VFYLSLSSITPDQGLANIICAQLLGAGGCISEVCLSSSIQQLQHQVLFLL   550
 551  DDYSGLASLPQALHTLITKNYLSRTCLLIAVHTNRVRDIRLYLGTSLEIQ   600
 601  EFPFYNTVSVLRKFFSHDIICVEKLIIYFIDNKDLQGVYKTPLFVAAVCT   650
 651  DWIQNASAQDKFQDVTLFQSYMQYLSLKYKATAEPLQATVSSCGQLALTG   700
 701  LFSSCFEFNSDDLAEAGVDEDEKLTTLLMSKFTAQRLRPVYRFLGPLFQE   750
 751  FLAAVRLTELLSSDRQEDQDLGLYYLRQIDSPLKAINSFNIFLYYVSSHS   800
 801  SSKAAPTVVSHLLQLVDEKESLENMSENEDYMKLHPQTFLWFQFVRGLWL   850
 851  VSPESSSSFVSEHLLRLALIFAYESNTVAECSPFILQFLRGKTLALRVLN   900
 901  LQYFRDHPESLLLLRSLKVSINGNKMSSYVDYSFKTYFENLQPPAIDEEY   950
 951  TSAFEHISEWRRNFAQDEEIIKNYENIRPRALPDISEGYWKLSPKPCKIP  1000
1001  KLEVQVNNTDAADQALLQVLMEVFSASQSIEFRLFNSSGFLESICPALEL  1050
1051  SKASVTKCSMSRLELSRAEQELLLTLPALQSLEVSETNQLPEQLFHNLHK  1100
1101  FLGLKELCVRLDGKPNVLSVLPREFPNLLHMEKLSIQTSTESDLSKLVKF  1150
1151  IQNFPNLHVFHLKCDFLSNCESLMAVLASCKKLREIEFSGRCFEAMTFVN  1200
1201  ILPNFVSLKILNLKDQQFPDKETSEKFAQALGSLRNLEELLVPTGDGIHQ  1250
1251  VAKLIVRQCLQLPCLRVLTFHDILDDDSVIEIARAATSGGFQKLENLDIS  1300
1301  MNHKITEEGYRNFFQALDNLPNLQELNICRNIPGRIQVQATTVKALGQCV  1350
1351  SRLPSLIRLHMLSWLLDEEDMKVINDVKERHPQSKRLIIFWKLIVPFSPV  1400
1401  ILE                                                 1403

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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