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

NucPred

Fetching Q9NYU2 from www.uniprot.org...

The NucPred score for your sequence is 0.45 (see score help below)

   1  MGCKGDASGACAAGALPVTGVCYKMGVLVVLTVLWLFSSVKADSKAITTS    50
  51  LTTKWFSTPLLLEASEFLAEDSQEKFWNFVEASQNIGSSDHDGTDYSYYH   100
 101  AILEAAFQFLSPLQQNLFKFCLSLRSYSATIQAFQQIAADEPPPEGCNSF   150
 151  FSVHGKKTCESDTLEALLLTASERPKPLLFKGDHRYPSSNPESPVVIFYS   200
 201  EIGSEEFSNFHRQLISKSNAGKINYVFRHYIFNPRKEPVYLSGYGVELAI   250
 251  KSTEYKAKDDTQVKGTEVNTTVIGENDPIDEVQGFLFGKLRDLHPDLEGQ   300
 301  LKELRKHLVESTNEMAPLKVWQLQDLSFQTAARILASPVELALVVMKDLS   350
 351  QNFPTKARAITKTAVSSELRTEVEENQKYFKGTLGLQPGDSALFINGLHM   400
 401  DLDTQDIFSLFDVLRNEARVMEGLHRLGIEGLSLHNVLKLNIQPSEADYA   450
 451  VDIRSPAISWVNNLEVDSRYNSWPSSLQELLRPTFPGVIRQIRKNLHNMV   500
 501  FIVDPAHETTAELMNTAEMFLSNHIPLRIGFIFVVNDSEDVDGMQDAGVA   550
 551  VLRAYNYVAQEVDDYHAFQTLTHIYNKVRTGEKVKVEHVVSVLEKKYPYV   600
 601  EVNSILGIDSAYDRNRKEARGYYEQTGVGPLPVVLFNGMPFEREQLDPDE   650
 651  LETITMHKILETTTFFQRAVYLGELPHDQDVVEYIMNQPNVVPRINSRIL   700
 701  TAERDYLDLTASNNFFVDDYARFTILDSQGKTAAVANSMNYLTKKGMSSK   750
 751  EIYDDSFIRPVTFWIVGDFDSPSGRQLLYDAIKHQKSSNNVRISMINNPA   800
 801  KEISYENTQISRAIWAALQTQTSNAAKNFITKMAKEGAAEALAAGADIAE   850
 851  FSVGGMDFSLFKEVFESSKMDFILSHAVYCRDVLKLKKGQRAVISNGRII   900
 901  GPLEDSELFNQDDFHLLENIILKTSGQKIKSHIQQLRVEEDVASDLVMKV   950
 951  DALLSAQPKGDPRIEYQFFEDRHSAIKLRPKEGETYFDVVAVVDPVTREA  1000
1001  QRLAPLLLVLAQLINMNLRVFMNCQSKLSDMPLKSFYRYVLEPEISFTSD  1050
1051  NSFAKGPIAKFLDMPQSPLFTLNLNTPESWMVESVRTPYDLDNIYLEEVD  1100
1101  SVVAAEYELEYLLLEGHCYDITTGQPPRGLQFTLGTSANPVIVDTIVMAN  1150
1151  LGYFQLKANPGAWILRLRKGRSEDIYRIYSHDGTDSPPDADEVVIVLNNF  1200
1201  KSKIIKVKVQKKADMVNEDLLSDGTSENESGFWDSFKWGFTGQKTEEVKQ  1250
1251  DKDDIINIFSVASGHLYERFLRIMMLSVLKNTKTPVKFWFLKNYLSPTFK  1300
1301  EFIPYMANEYNFQYELVQYKWPRWLHQQTEKQRIIWGYKILFLDVLFPLV  1350
1351  VDKFLFVDADQIVRTDLKELRDFNLDGAPYGYTPFCDSRREMDGYRFWKS  1400
1401  GYWASHLAGRKYHISALYVVDLKKFRKIAAGDRLRGQYQGLSQDPNSLSN  1450
1451  LDQDLPNNMIHQVPIKSLPQEWLWCETWCDDASKKRAKTIDLCNNPMTKE  1500
1501  PKLEAAVRIVPEWQDYDQEIKQLQIRFQKEKETGALYKEKTKEPSREGPQ  1550
1551  KREEL                                               1555

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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