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

NucPred

Fetching P63135 from www.uniprot.org...

The NucPred score for your sequence is 0.67 (see score help below)

   1  NKSRKRRNRLSFLGAATVEPPKPIPLTWKTEKPVWVNQWPLPKQKLEALH    50
  51  LLANEQLEKGHIEPSFSPWNSPVFVIQKKSGKWRMLTDLRAVNAVIQPMG   100
 101  PLQPGLPSPAMIPKDWPLIIIDLKDCFFTIPLAEQDCEKFAFTIPAINNK   150
 151  EPATRFQWKVLPQGMLNSPTICQTFVGRALQPVREKFSDCYIIHYIDDIL   200
 201  CAAETRDKLIDCYTFLQAEVANAGLAIASDKIQTSTPFHYLGMQIENRKI   250
 251  KQQKIEIRKDTLKTLNDFQKLLGDINWIRPTLGIPTYAMSNLFSILRGDS   300
 301  DLNSKRILTPEATKEIKLVEEKIQSAQINRIDPLAPLQLLIFATAHSPTG   350
 351  IIIQNTDLVEWSFLPHSTVKTFTLYLDQIATLIGQTRLRIIKLCGNDPDK   400
 401  IVVPLTKEQVRQAFINSGAWQIGLANFVGIIDNHYPKTKIFQFLKLTTWI   450
 451  LPKITRREPLENALTVFTDGSSNGKAAYTGPKERVIKTPYQSAQRAELVA   500
 501  VITVLQDFDQPINIISDSAYVVQATRDVETALIKYSMDDQLNQLFNLLQQ   550
 551  TVRKRNFPFYITHIRAHTNLPGPLTKANEQADLLVSSALIKAQELHALTH   600
 601  VNAAGLKNKFDVTWKQAKDIVQHCTQCQILHLPTQEAGVNPRGLCPNALW   650
 651  QMDVTHVPSFGRLSYVHVTVDTYSHFIWATCQTGESTSHVKKHLLSCFAV   700
 701  MGVPEKIKTDNGPGYCSKAFQKFLSQWKISHTTGIPYNSQGQAIVERTNR   750
 751  TLKTQLVKQKEGGDSKECTTPQMQLNLALYTLNFLNIYRNQTTTSAEQHL   800
 801  TGKKNSPHEGKLIWWKDNKNKTWEIGKVITWGRGFACVSPGENQLPVWIP   850
 851  TRHLKFYNEPIGDAKKRASTEMVTPVTWMDNPIEIYVNDSVWVPGPIDDR   900
 901  CPAKPEEEGMMINISIGYRYPPICLGRAPGCLMPAVQNWLVEVPTVSPIS   950
 951  RFTYHMVSGMSLRPRVNYLQDFSYQRSLKFRPKGKPCPKEIPKESKNTEV  1000
1001  LVWEECVANSAVILQNNEFGTIIDWAPRGQFYHNCSGQTQSCPSAQVSPA  1050
1051  VDSDLTESLDKHKHKKLQSFYPWEWGEKGISTPRPKIVSPVSGPEHPELW  1100
1101  RLTVASHHIRIWSGNQTLETRDCKPFYTIDLNSSLTVPLQSCVKPPYMLV  1150
1151  VGNIVIKPDSQTITCENCRLLTCIDSTFNWQHRILLVRAREGVWIPVSMD  1200
1201  RPWEASPSVHILTEVLKGVLNRSKRFIFTLIAVIMGLIAVTATAAVAGVA  1250
1251  LHSSVQSVNFVNDWQKNSTRLWNSQSSIDQKLANQINDLRQTVIWMGDRL  1300
1301  MSLEHRFQLQCDWNTSDFCITPQIYNESEHHWDMVRRHLQGREDNLTLDI  1350
1351  SKLKEQIFEASKAHLNLVPGTEAIAGVADGLANLNPVTWVKTIGSTTIIN  1400
1401  LILILVCLFCLLLVCRCTQQLRRDSDHRERAMMTMAVLSKRKGGNVGKSK  1450
1451  RDQIVTVSV                                           1459

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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