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

NucPred

Fetching O88923 from www.uniprot.org...

The NucPred score for your sequence is 0.47 (see score help below)

   1  MVSSGCRMRSLWFIMIISFSPNTEGFSRAALPFGLVRRELSCEGYSIDLR    50
  51  CPGSDVIMIESANYGRTDDKICDADPFQMENTDCYLPDAFKIMTQRCNNR   100
 101  TQCVVVTGSDVFPDPCPGTYKYLEVQYECVPYMEQKVFVCPGTLKAIVDS   150
 151  PSIYEAEQKAGAWCKDPLQAADKIYFMPWTPYRTDTLIEYASLEDFQNSR   200
 201  QTTTYKLPNRVDGTGFVVYDGAVFFNKERTRNIVKFDLRTRIKSGEAIIN   250
 251  YANYHDTSPYRWGGKTDIDLAVDENGLWVIYATEQNNGMIVISQLNPYTL   300
 301  RFEATWETTYDKRAASNAFMICGVLYVVRSVYQDNESEAGKNVIDYIYNT   350
 351  RLSRGEHVDVPFPNQYQYIAAVDYNPRDNQLYVWNNNFILRYSLEFGPPD   400
 401  PAQVPTTAVTITSSAELFKTTVSTTSSTSQRGPVSSTVAGPQEGSRGTKP   450
 451  PPAVSTTKIPPVTNIFPLPERFCEALEMKGIKWPQTQRGMMVERPCPKGT   500
 501  RGTASYLCMASTGTWNPKGPDLSNCTSHWVNQLAQKIRSGENAASLANEL   550
 551  AKHTKGTVFAGDVSSSVRLMEQLVDILDAQLQELKPSEKDSAGRSYNKLQ   600
 601  KREKTCRAYLKAIVDTVDNLLRAETLDCWKHMNSSEQAHTATMLLDTLEE   650
 651  GAFVLADNLLEPTRVSMPTDNIVLEVAVLSTEGQVQDFTFHLGFKGAFSS   700
 701  IQLSANTVKQNSRNGLAKVVFIIYRSLGPFLSTENATVKLGADLLGRNST   750
 751  IAVNSHVLSVSINKESSRVYLTDPVLFSMPHIDSDNYFNANCSFWNYSER   800
 801  TMMGYWSTQGCKLVDTNKTRTTCACSHLTNFAILMAHREIVYKDGVHKLL   850
 851  LTVITWVGIVVSLVCLAICIFTFCFFRGLQSDRNTIHKNLCINLFIAEFI   900
 901  FLIGIDKTQYTIACPVFAGLLHFFFLAAFSWMCLEGVQLYLMLVEVFESE   950
 951  YSRKKYYYVAGYLFPATVVGVSAAIDSKSYGTLEACWLHVDNYFIWSFIG  1000
1001  PVTFIILLNIIFLVITLCKMVKHSNTLKPDSSRLENINNYRVCDGYYNTD  1050
1051  LPGYEDNKPFIKSWVLGAFALLCLLGLTWSFGLLFVNEETVVMAYLFTAF  1100
1101  NAFQGLFIFIFHCALQKKVRKEYAKCFRHWYCCGGLPTESPHSSVKASTS  1150
1151  RTSARYSSGTQSRIRRMWNDTVRKQSESSFISGDINSTSTLNQGMTGNYL  1200
1201  LTNPLLRPHGTNNPYNTLLAETVVCNAPSAPVFNSPGHSLNNTRDTSAMD  1250
1251  TLPLNGNFNNSYSLRKADYHDGVQVVDCGLSLNDTAFEKMIISELVHNNL  1300
1301  RGSNKTHNLELKLPVKPVIGGSSSEDDAIVADASSLMHGDNPGLEFRHKE  1350
1351  LEAPLIPQRTHSLLYQPQKKVKPEATDSYVSQLTAEADEHLQSPNRDSLY  1400
1401  TSMPNLRDSPYPESSPDMAEDLSPSRRSENEDIYYKSMPNLGAGRQLQMC  1450
1451  YQISRGNSDGYIIPINKEGCIPEGDVREGQMQLVTSL               1487

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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