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

NucPred

Fetching Q2UVX4 from www.uniprot.org...

The NucPred score for your sequence is 0.53 (see score help below)

   1  MKPTSGPSLLLLLLASLPMALGNPMYSMITPNILRLESEETVVLEAHGGQ    50
  51  GTIQVSVTVHDFPAKKQVLSNENTQLNSNNGYLSTVTIKIPASKELKSDK   100
 101  GHKFVTVVATFGNVQVEKVVLISLQSGYLFIQTDKTIYTPGSTVLYRVFT   150
 151  VDHKLLPVGQTVFITIETPDGIPVKRDSKSSQNQFGILTLSWNIPELVNM   200
 201  GVWKIKAYYEDSPQQVFSAEFEVKEYVLPSFEVQLEPEEKFYYIDDPDGL   250
 251  KVNIIARFLYGEQVDGTAFVIFGVQDGDRRISLTHSLTRVPINDGNGEAI   300
 301  LKRQVLLNGVQPSRADALVGKSIYVSATVILQSGSDMVEAERTGIPIVTS   350
 351  PYQIHFTKTPKFFKPAMPFDLMVYVTNPDGSPARHIPVVTQGSNVQSLTQ   400
 401  DDGVAKLSINTQNKRDPLTITVRTKKDNIPEGRQATRTMQALPYNTQGNS   450
 451  NNYLHLSVPRVELKPGETLNVNFHLRTDPGEQAKIRYYTYMIMNKGKLLK   500
 501  VGRQYREPGQDLVVLPLTITSDFIPSFRLVAYYTLINAKGQREVVADSVW   550
 551  VDVKDSCMGTLVVKNGGKEEKHHRPGQQITLKIEADQGARVGLVAVDKGV   600
 601  FVLNKKNKLTQRKIWDVVEKADIGCTPGSGRNYAGVFTDAGLTLKTSQGL   650
 651  ETQQRADPQCPQPATRRRRSVQLMEKRMDKAGQYSSDLRKCCEDGMRDNP   700
 701  MKFPCQRRAQFILQGDACVKAFLDCCEYITQLRQQHSRDGALELARSDLD   750
 751  DDIIPEEDIISRSQFPESWLWTVIEDLKQADKNGISTKLMNVFLKDSITT   800
 801  WEILAVSLSDKKGICVADPYEVTVMQDFFIDLRLPYSVVRNEQVEIRAIL   850
 851  YNYREAENLKVRVELLYNPAFCSLATAKKRHQQTITIPARSSVAVPYVIV   900
 901  PLKIGLHEVEVKAAVYNHFISDGVKKTLKVVPEGVRVNKTVAVRTLNPEH   950
 951  LGQGGVQREEVPAADLSDQVPDTESETKILLQGTPVAQMTEDAIDGERLK  1000
1001  HLIQTPSGCGEQNMIGMTPTVIAVHYLDSTDQWEKFGLEKRQESLELIRK  1050
1051  GYTQQLAFRQKSSAYAAFQYRPPSTWLTAYVVKVFALAANLIAIDSKDLC  1100
1101  ETVKWLILEKQKPDGIFQEDGPVIHQEMIGGFRDTREKDVSLTAFVLIAL  1150
1151  HEAKDICEAQVNSLGRSIAKAGDFLENHYRELRRPYTVAIAAYALALLGK  1200
1201  LEGDRLTKFLNTAKEKNRWEEPNQKLYNVEATSYALLALLARKDYDTTPP  1250
1251  VVRWLNEQRYYGGGYGSTQATFMVFQALAQYQKDVPDHKELNLDVSIQLP  1300
1301  SRNSAVRHRILWESASLLRSEETKENERFTVKAEGKGQGTLSVVTVYHAK  1350
1351  LKGKVSCKKFDLRVSIRPAPETVKKPQDAKGSMILDICTKYLGDQDATMS  1400
1401  ILDISMMTGFSPDVEDLKTLSTGVDRYISKYEMNRDSNKNTLIIYLDKVS  1450
1451  HTVEDCLSFKVHQYFNVGLIQPGAVKVYSYYNLDETCIRFYHPDKEDGML  1500
1501  SKLCHKDTCRCAEENCFMHHTEKEVTLEDRLDKACEPGVDYVYKTRLIQK  1550
1551  KLEDDFDEYIMVIENIIKSGSDEVQVKQERKFISHIKCREALKLKEGAHY  1600
1601  LVWGVSSDLWGEKPKISYIIGKDTWVELWPEAEECQDEENQKQCEDLANF  1650
1651  TENMVVFGCPN                                         1661

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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