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

NucPred

Fetching Q9QXL2 from www.uniprot.org...

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

   1  MLGAADESSVRVAVRIRPQLAKEKIEGCHICTSVTPGEPQVFLGKDKAFT    50
  51  FDYVFDIDSQQEQIYTQCIEKLIEGCFEGYNATVFAYGQTGAGKTYTMGT   100
 101  GFDVNIMEEEQGIISRAVRHLFKSIDEKKTSAIKNGLPPPEFKVNAQFLE   150
 151  LYNEEVLDLFDTTRDIDAKNKKSNIRIHEDSTGGIYTVGVTTRTVNTEPE   200
 201  MMQCLKLGALSRTTASTQMNVQSSRSHAIFTIHVCQTRVCPQTDAENATD   250
 251  NKLISESSPMNEFETLTAKFHFVDLAGSERLKRTGATGERAKEGISINCG   300
 301  LLALGNVISALGDKSKRATHVPYRDSKLTRLLQDSLGGNSQTIMIACVSP   350
 351  SDRDFMETLNTLKYANRARNIKNKVMVNQDRASQQINALRSEITRLQMEL   400
 401  MEYKTGKRIIDEEGVESINDMFHENAMLQTENNNLRVRIKAMQETVDALR   450
 451  ARITQLVSEQANQVLARAGEGNEEISNMIHSYIKEIEDLRAKLLESEAVN   500
 501  ENLRKNLTRATARSPYFSASSAFSPTILSSDKETIEIIDLAKKDLEKLKR   550
 551  KEKKKKKRLQKLEESGREERSVAGKDDNADTDQEKKEEKGVSEKENNELD   600
 601  VEENQEVSDHEDEEEEEEDEEEEDDIEGEESSDESDSESDEKANYQADLA   650
 651  NITCEIAIKQKLIDELENSQKRLQTLKKQYEEKLMMLQHKIRDTQLERDQ   700
 701  VLQNLGSVESYSEEKAKKVKCEYEKKLHAMNKELQRLQTAQKEHARLLKN   750
 751  QSQYEKQLKKLQQDVMEMKKTKVRLMKQMKEEQEKARLTESRRNREIAQL   800
 801  KKDQRKRDHQLRLLEAQKRNQEVVLRRKTEEVTALRRQVRPMSDKVAGKV   850
 851  TRKLSSSESPAPDTGSSAASGEADTSRPGTQQKMRIPVARVQALPTPTTN   900
 901  GTRKKYQRKGFTGRVFTSKTARMKWQLLERRVTDIIMQKMTISNMEADMN   950
 951  RLLRQREELTKRREKLSKRREKIVKESGEGDKSVANIIEEMESLTANIDY  1000
1001  INDSIADCQANIMQMEEAKEEGETLDVTAVINACTLTEARYLLDHFLSMG  1050
1051  INKGLQAAQKEAQIKVLEGRLKQTEITSATQNQLLFHMLKEKAELNPELD  1100
1101  ALLGHALQDLDGAPPENEEDSSEEDGPLHSPGSEGSTLSSDLMKLCGEVK  1150
1151  PKNKARRRTTTQMELLYADSSEVASDTSAGDASLSGPLAPVAEGQEIGMN  1200
1201  TETSGTSARDKELLAPSGLPSKIGSISRQSSLSEKKVPEPSPVTRRKAYE  1250
1251  KADKPKAKEHKHSDSGASETSLSPPSSPPSRPRNELNVFNRLTVPQGTPS  1300
1301  VQQDKSDESDSSLSEVHRGIINPFPACKGVRASPLQCVHIAEGHTKAVLC  1350
1351  VDSTDDLLFTGSKDRTCKVWNLVTGQEIMSLGVHPNNVVSVKYCNYTSLV  1400
1401  FTVSTSYIKVWDIRESAKCIRTLTSSGQVTLGEACSASTSRTVAIPSGES  1450
1451  QINQIALNPTGTFLYAASGNAVRMWDLKRFQSTGKLTGHLGPVMCLTVDQ  1500
1501  ISNGQDLIITGSKDHYIKMFDVTEGALGTVSPTHNFEPPHYDGIEALAIQ  1550
1551  GDNLFSGSRDNGIKKWDLAQKGLLQQVPNAHKDWVCALGLVPGHPVLLSG  1600
1601  CRGGILKLWNVDTFVPVGEMRGHDSPINAICVNSTHVFTAADDRTVRIWK  1650
1651  AHNLQDGQLSDTGDLGEDIASN                              1672

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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