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

NucPred

Fetching Q13075 from www.uniprot.org...

The NucPred score for your sequence is 0.57 (see score help below)

   1  MATQQKASDERISQFDHNLLPELSALLGLDAVQLAKELEEEEQKERAKMQ    50
  51  KGYNSQMRSEAKRLKTFVTYEPYSSWIPQEMAAAGFYFTGVKSGIQCFCC   100
 101  SLILFGAGLTRLPIEDHKRFHPDCGFLLNKDVGNIAKYDIRVKNLKSRLR   150
 151  GGKMRYQEEEARLASFRNWPFYVQGISPCVLSEAGFVFTGKQDTVQCFSC   200
 201  GGCLGNWEEGDDPWKEHAKWFPKCEFLRSKKSSEEITQYIQSYKGFVDIT   250
 251  GEHFVNSWVQRELPMASAYCNDSIFAYEELRLDSFKDWPRESAVGVAALA   300
 301  KAGLFYTGIKDIVQCFSCGGCLEKWQEGDDPLDDHTRCFPNCPFLQNMKS   350
 351  SAEVTPDLQSRGELCELLETTSESNLEDSIAVGPIVPEMAQGEAQWFQEA   400
 401  KNLNEQLRAAYTSASFRHMSLLDISSDLATDHLLGCDLSIASKHISKPVQ   450
 451  EPLVLPEVFGNLNSVMCVEGEAGSGKTVLLKKIAFLWASGCCPLLNRFQL   500
 501  VFYLSLSSTRPDEGLASIICDQLLEKEGSVTEMCVRNIIQQLKNQVLFLL   550
 551  DDYKEICSIPQVIGKLIQKNHLSRTCLLIAVRTNRARDIRRYLETILEIK   600
 601  AFPFYNTVCILRKLFSHNMTRLRKFMVYFGKNQSLQKIQKTPLFVAAICA   650
 651  HWFQYPFDPSFDDVAVFKSYMERLSLRNKATAEILKATVSSCGELALKGF   700
 701  FSCCFEFNDDDLAEAGVDEDEDLTMCLMSKFTAQRLRPFYRFLSPAFQEF   750
 751  LAGMRLIELLDSDRQEHQDLGLYHLKQINSPMMTVSAYNNFLNYVSSLPS   800
 801  TKAGPKIVSHLLHLVDNKESLENISENDDYLKHQPEISLQMQLLRGLWQI   850
 851  CPQAYFSMVSEHLLVLALKTAYQSNTVAACSPFVLQFLQGRTLTLGALNL   900
 901  QYFFDHPESLSLLRSIHFPIRGNKTSPRAHFSVLETCFDKSQVPTIDQDY   950
 951  ASAFEPMNEWERNLAEKEDNVKSYMDMQRRASPDLSTGYWKLSPKQYKIP  1000
1001  CLEVDVNDIDVVGQDMLEILMTVFSASQRIELHLNHSRGFIESIRPALEL  1050
1051  SKASVTKCSISKLELSAAEQELLLTLPSLESLEVSGTIQSQDQIFPNLDK  1100
1101  FLCLKELSVDLEGNINVFSVIPEEFPNFHHMEKLLIQISAEYDPSKLVKL  1150
1151  IQNSPNLHVFHLKCNFFSDFGSLMTMLVSCKKLTEIKFSDSFFQAVPFVA  1200
1201  SLPNFISLKILNLEGQQFPDEETSEKFAYILGSLSNLEELILPTGDGIYR  1250
1251  VAKLIIQQCQQLHCLRVLSFFKTLNDDSVVEIAKVAISGGFQKLENLKLS  1300
1301  INHKITEEGYRNFFQALDNMPNLQELDISRHFTECIKAQATTVKSLSQCV  1350
1351  LRLPRLIRLNMLSWLLDADDIALLNVMKERHPQSKYLTILQKWILPFSPI  1400
1401  IQK                                                 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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