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

NucPred

Fetching Q9Y2L5 from www.uniprot.org...

The NucPred score for your sequence is 0.60 (see score help below)

   1  MAQCVQSVQELIPDSFVPCVAALCSDEAERLTRLNHLSFAELLKPFSRLT    50
  51  SEVHMRDPNNQLHVIKNLKIAVSNIVTQPPQPGAIRKLLNDVVSGSQPAE   100
 101  GLVANVITAGDYDLNISATTPWFESYRETFLQSMPALDHEFLNHYLACML   150
 151  VASSSEAEPVEQFSKLSQEQHRIQHNSDYSYPKWFIPNTLKYYVLLHDVS   200
 201  AGDEQRAESIYEEMKQKYGTQGCYLLKINSRTSNRASDEQIPDPWSQYLQ   250
 251  KNSIQNQESYEDGPCTITSNKNSDNNLLSLDGLDNEVKDGLPNNFRAHPL   300
 301  QLEQSSDPSNSIDGPDHLRSASSLHETKKGNTGIIHGACLTLTDHDRIRQ   350
 351  FIQEFTFRGLLPHIEKTIRQLNDQLISRKGLSRSLFSATKKWFSGSKVPE   400
 401  KSINDLKNTSGLLYPPEAPELQIRKMADLCFLVQHYDLAYSCYHTAKKDF   450
 451  LNDQAMLYAAGALEMAAVSAFLQPGAPRPYPAHYMDTAIQTYRDICKNMV   500
 501  LAERCVLLSAELLKSQSKYSEAAALLIRLTSEDSDLRSALLLEQAAHCFI   550
 551  NMKSPMVRKYAFHMILAGHRFSKAGQKKHALRCYCQAMQVYKGKGWSLAE   600
 601  DHINFTIGRQSYTLRQLDNAVSAFRHILINESKQSAAQQGAFLREYLYVY   650
 651  KNVSQLSPDGPLPQLPLPYINSSATRVFFGHDRRPADGEKQAATHVSLDQ   700
 701  EYDSESSQQWRELEEQVVSVVNKGVIPSNFHPTQYCLNSYSDNSRFPLAV   750
 751  VEEPITVEVAFRNPLKVLLLLTDLSLLWKFHPKDFSGKDNEEVKQLVTSE   800
 801  PEMIGAEVISEFLINGEESKVARLKLFPHHIGELHILGVVYNLGTIQGSM   850
 851  TVDGIGALPGCHTGKYSLSMSVRGKQDLEIQGPRLNNTKEEKTSVKYGPD   900
 901  RRLDPIITEEMPLLEVFFIHFPTGLLCGEIRKAYVEFVNVSKCPLTGLKV   950
 951  VSKRPEFFTFGGNTAVLTPLSPSASENCSAYKTVVTDATSVCTALISSAS  1000
1001  SVDFGIGTGSQPEVIPVPLPDTVLLPGASVQLPMWLRGPDEEGVHEINFL  1050
1051  FYYESVKKQPKIRHRILRHTAIICTSRSLNVRATVCRSNSLENEEGRGGN  1100
1101  MLVFVDVENTNTSEAGVKEFHIVQVSSSSKHWKLQKSVNLSENKDTKLAS  1150
1151  REKGKFCFKAIRCEKEEAATQSSEKYTFADIIFGNEQIISSASPCADFFY  1200
1201  RSLSSELKKPQAHLPVHTEKQSTEDAVRLIQKCSEVDLNIVILWKAYVVE  1250
1251  DSKQLILEGQHHVILRTIGKEAFSYPQKQEPPEMELLKFFRPENITVSSR  1300
1301  PSVEQLSSLIKTSLHYPESFNHPFHQKSLCLVPVTLLLSNCSKADVDVIV  1350
1351  DLRHKTTSPEALEIHGSFTWLGQTQYKLQLKSQEIHSLQLKACFVHTGVY  1400
1401  NLGTPRVFAKLSDQVTVFETSQQNSMPALIIISNV                 1435

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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