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

NucPred

Fetching Q99PL5 from www.uniprot.org...

The NucPred score for your sequence is 0.82 (see score help below)

   1  MDIYDTQTLGVVVFGGFMVVSAIGIFLVSTFSMKETSYEEALANQRKEMA    50
  51  KTHHQKGEKKKKEKTVEKKGKTKKKEEKPNGKIPEHDLDPNVTIILKEPV   100
 101  RVSAVAVAPTSVHSSVGHTPIATVPAMPQEKLASSPKDRKKKEKKVAKVE   150
 151  PAVSSIVNSIQVLASKSAILEATPKEVPMVAVPPVGSKASSPATSSQGKK   200
 201  GQGAQNQAKKGEGAQNQGKKGEGAQNQAKKGEGAQNQAKKGEGAQNQGKK   250
 251  GEGAQNQAKKGEGGQNQAKKGEGAQNQGKKGEGAQNQGKKGEGAQNQAKK   300
 301  GEGAQNQAKKGEGAQNQGKKGEGAQNQSKKGEGAQNQAKKGEGGQNQAKK   350
 351  GEGAQNQAKKGEGAQNQAKKGEGVQNQAKKGVEGAQNQGKKGEANQNQAK   400
 401  KGEGGQNQTKKGEGPQNQGKKGEAAQKQDKKIEGAQNQGKKPEGTSNQGK   450
 451  KGEGAQNQGKKGEGAQNQSKKGEGAQNQAKKGEGGQNQAKKGEGAQNQAK   500
 501  KGEGAQNQAKKGEGVQNQAKKGVEGAQNQGKKGEANQNQAKKGEGGQNQT   550
 551  KKGEGPQNQGKKGEAAQKQDKKIEGAQNQGKKPEGTSNQGKKGEGAQNQG   600
 601  KKGEGAQNQGKKGEGAQNQGKKGEGAQNQGKKGEGAQNQGKKGEGAQNQG   650
 651  KKGEGAQNQGKKGEGPQNQAKKGEGAQNQGKKGEGAQNQGKKGEGAQNQG   700
 701  KKAEGVQSQSKKGEGTQNQGKKGDGNPNQGKKGEGASNQNRKTDTVANQG   750
 751  TKQEGVSNQVKKSEGSPNQGKKAEGAPNQGKKKDGSPSQAKKVDAAANQG   800
 801  KKSEMAPAQGQKASMVQSQEAPKQDAPAKKKSGSRKKGEPGPPDCDGPLF   850
 851  LPYKTLVSTVGSMVFSEGEAQRLIEILSEKTGVIQDTWHKATQKGDPVAI   900
 901  LKRQLQEKEKLLATEQEDAAVAKSKLRELNKEMASEKAKAAAGEAKVKKQ   950
 951  LVAREQEIAAVQARMQASYRDHVKEVQQLQGKIRTLQEQLENGPNTQLAR  1000
1001  LQQENSILRDALNQATSQVESKQNTELAKLRQELSKVNKELVEKSEASRQ  1050
1051  EEQQRKALEAKAATFEKQVLQLQASHKESEEALQKRLEEVTRELCRAQTS  1100
1101  HANLRADAEKAQEQQQRVAELHSKLQSSEVEVKSKCEELSSLHGQLKEAR  1150
1151  AENSQLTERIRSIEALLEAGQAQDTQASHAEANQQQTRLKELESQVSCLE  1200
1201  KETSELKEAMEQQKGKNNDLREKNWKAMEALALAERACEEKLRSLTQAKE  1250
1251  ESEKQLHLAEAQTKETLLALLPGLSISAHQNYAEWLQEFKEKGSELLKKP  1300
1301  PTLEPSMDIVLKLREAEETQNSLQAECDQYRTILAETEGMLKDLQKSVEE  1350
1351  EERVWKAKVGAAEEELHKSRVTVKHLEDIVEKLKGELESSDQVREHTSHL  1400
1401  EAELEKHMAAASAECQNYAKEVAGLRQLLLESQSQLDEAKSEAQKQSDEL  1450
1451  ALVRQQLSDMRSHVEDGDVAGSPAVPPAEQDPMKLKTQLERTEATLEAEQ  1500
1501  TRRQKLTAEFEEAQRTACRIQEELEKLRAAGPLESSGKEEITQLKERLEK  1550
1551  EKRLTSDLGRAAIKLQELLKTTQEQLTKEKDTVKKLQEQLGKAEDGSSSK  1600
1601  EGTSV                                               1605

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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