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

NucPred

Fetching Q9ULU8 from www.uniprot.org...

The NucPred score for your sequence is 0.87 (see score help below)

   1  MLDPSSSEEESDEIVEEESGKEVLGSAPSGARLSPSRTSEGSAGSAGLGG    50
  51  GGAGAGAGVGAGGGGGSGASSGGGAGGLQPSSRAGGGRPSSPSPSVVSEK   100
 101  EKEELERLQKEEEERKKRLQLYVFVMRCIAYPFNAKQPTDMARRQQKISK   150
 151  QQLQTVKDRFQAFLNGETQIMADEAFMNAVQSYYEVFLKSDRVARMVQSG   200
 201  GCSANDSREVFKKHIEKRVRSLPEIDGLSKETVLSSWMAKFDAIYRGEED   250
 251  PRKQQARMTASAASELILSKEQLYEMFQNILGIKKFEHQLLYNACQLDNP   300
 301  DEQAAQIRRELDGRLQMADQIARERKFPKFVSKEMENMYIEELKSSVNLL   350
 351  MANLESMPVSKGGEFKLQKLKRSHNASIIDMGEESENQLSKSDVVLSFSL   400
 401  EVVIMEVQGLKSLAPNRIVYCTMEVEGGEKLQTDQAEASKPTWGTQGDFS   450
 451  TTHALPAVKVKLFTESTGVLALEDKELGRVILHPTPNSPKQSEWHKMTVS   500
 501  KNCPDQDLKIKLAVRMDKPQNMKHSGYLWAIGKNVWKRWKKRFFVLVQVS   550
 551  QYTFAMCSYREKKAEPQELLQLDGYTVDYTDPQPGLEGGRAFFNAVKEGD   600
 601  TVIFASDDEQDRILWVQAMYRATGQSHKPVPPTQVQKLNAKGGNVPQLDA   650
 651  PISQFYADRAQKHGMDEFISSNPCNFDHASLFEMVQRLTLDHRLNDSYSC   700
 701  LGWFSPGQVFVLDEYCARNGVRGCHRHLCYLRDLLERAENGAMIDPTLLH   750
 751  YSFAFCASHVHGNRPDGIGTVTVEEKERFEEIKERLRVLLENQITHFRYC   800
 801  FPFGRPEGALKATLSLLERVLMKDIVTPVPQEEVKTVIRKCLEQAALVNY   850
 851  SRLSEYAKIEENQKDAENVGRLITPAKKLEDTIRLAELVIEVLQQNEEHH   900
 901  AEPHVDKGEAFAWWSDLMVEHAETFLSLFAVDMDAALEVQPPDTWDSFPL   950
 951  FQLLNDFLRTDYNLCNGKFHKHLQDLFAPLVVRYVDLMESSIAQSIHRGF  1000
1001  ERESWEPVKSLTSNLPNVNLPNVNLPKVPNLPVNIPLGIPQMPTFSAPSW  1050
1051  MAAIYDADNGSGTSEDLFWKLDALQTFIRDLHWPEEEFGKHLEQRLKLMA  1100
1101  SDMIESCVKRTRIAFEVKLQKTSRSTDFRVPQSICTMFNVMVDAKAQSTK  1150
1151  LCSMEMGQEHQYHSKIDELIEETVKEMITLLVAKFVTILEGVLAKLSRYD  1200
1201  EGTLFSSFLSFTVKAASKYVDVPKPGMDVADAYVTFVRHSQDVLRDKVNE  1250
1251  EMYIERLFDQWYNSSMNVICTWLTDRMDLQLHIYQLKTLIRMVKKTYRDF  1300
1301  RLQGVLDSTLNSKTYETIRNRLTVEEATASVSEGGGLQGISMKDSDEEDE  1350
1351  EDD                                                 1353

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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