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

NucPred

Fetching Q74Z27 from www.uniprot.org...

The NucPred score for your sequence is 0.99 (see score help below)

   1  MSLEALLNKEEKGSGAAREAFMRRMNERFNSVCHKDAREQQYQDWKYLSY    50
  51  QEFELVNEWSAASRELTVNQCGQLLSNVKSAQAEWLAYEEFVAGRARLVA   100
 101  EVEAKREREQEEQEERQPARAKTKERARARGTAKRAVGRKATKAPAAPAE   150
 151  QEGGVPAARAAAKAPVRAEGAAEPPLKRELSGAKLEDEGEGEDDDEEEDE   200
 201  DDEDDEDEDEDEDEEEEEEEELEELEDIQLLDDDNDKDFSPEGGRSKSSI   250
 251  KLNTKLDINSDIALIQRELLKMAQKHKSAKAKKRKFTSCVVQRYDSDHTR   300
 301  LEVKVTLKQLHIKRLKRLLNEAKRKRAAEEALAANEQQGNLAKRRKTAQK   350
 351  QKPAANGAPAASSSEDVTVTEAATPVPAKVNGEAPSNESPVAAIPDINPT   400
 401  TGLPTYGMKMTAKEARAIQRHYDTTYITVWKDMARKDSAKLSRLVQQIQS   450
 451  IRSANFKKTSSLVAREARKWQSRNFRQVKDFQTRARRGVREMSSFWKKNE   500
 501  REERELKKRAEREAIEQAKKEEEERESKRQARKLNFLLTQTELYSHFIGS   550
 551  KIKTNELEGNMADSNLATAPDVSAIDLSKPPTRKNEVHTIDFDNEDDEEL   600
 601  HRKAAQNASNALKETREKAKAFDGMSGDDEELNFQNPTSLGEITIEQPKI   650
 651  LACTLKEYQLKGLNWLANLYDQGINGILADEMGLGKTVQSISVLAHLAER   700
 701  YNIWGPFIVVTPASTLHNWVNEIQKFVPDFKILPYWGNGNDRKILRRFWD   750
 751  RKHLRYSKDAPFHVMITSYQMIVSDAAYLQKMKWQYMILDEAQAIKSSQS   800
 801  SRWKNLLSFHCRNRLLLTGTPIQNSMQELWALLHFIMPSLFDSHDEFNDW   850
 851  FSKDIESHAQSNTQLNQQQLRRLHMILKPFMLRRIKKNVQSELGDKIEID   900
 901  VMCDLTHRQAKLYQVLKSQVSASYDAIENAASNSSGDDSGNMSLSDSKIM   950
 951  NTVMEFRKVCNHPDLFERADVSSPFSFTSFGQTGSIMREGDVIDVQYSSK  1000
1001  NPVSFHLPRLIYDDLILPNYNHDSDMRTKILNHMMSIFAPANSPDLCATL  1050
1051  SKVAGVEPNSILRLSQEHIVKRAIDLSAHSPNVTRSGIFSVVYEDDKSSL  1100
1101  SSLDKTLLINDKSDYLHTIARTTQNGVLASLLNIQGNFYENEYMNVLRPA  1150
1151  YRPAAAAPPISIHVMGSSNFSIKRDNALFEPYITRSLGIIPPELQTRLTE  1200
1201  KENNIFTALPISELYPAPLNKSFSSYISMPSMDRFITESAKLKKLDELLV  1250
1251  RLKAGEHRVLIYFQMTRMMDLIEEYLTYRQYKHIRLDGSSKLEDRRDLVH  1300
1301  DWQTKSDIFIFLLSTRAGGLGINLTSADTVIFYDSDWNPTIDSQAMDRAH  1350
1351  RLGQTKQVTVYRLLIKGTIEERMRDRAKQKEHVQQVVMEGKTKENNVQTI  1400
1401  TANGKTLENLPLPL                                      1414

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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