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

NucPred

Fetching Q5TAX3 from www.uniprot.org...

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

   1  MEESKTLKSENHEPKKNVICEESKAVQVIGNQTLKARNDKSVKEIENSSP    50
  51  NRNSSKKNKQNDICIEKTEVKSCKVNAANLPGPKDLGLVLRDQSHCKAKK   100
 101  FPNSPVKAEKATISQAKSEKATSLQAKAEKSPKSPNSVKAEKASSYQMKS   150
 151  EKVPSSPAEAEKGPSLLLKDMRQKTELQQIGKKIPSSFTSVDKVNIEAVG   200
 201  GEKCALQNSPRSQKQQTCTDNTGDSDDSASGIEDVSDDLSKMKNDESNKE   250
 251  NSSEMDYLENATVIDESALTPEQRLGLKQAEERLERDHIFRLEKRSPEYT   300
 301  NCRYLCKLCLIHIENIQGAHKHIKEKRHKKNILEKQEESELRSLPPPSPA   350
 351  HLAALSVAVIELAKEHGITDDDLRVRQEIVEEMSKVITTFLPECSLRLYG   400
 401  SSLTRFALKSSDVNIDIKFPPKMNHPDLLIKVLGILKKNVLYVDVESDFH   450
 451  AKVPVVVCRDRKSGLLCRVSAGNDMACLTTDLLTALGKIEPVFIPLVLAF   500
 501  RYWAKLCYIDSQTDGGIPSYCFALMVMFFLQQRKPPLLPCLLGSWIEGFD   550
 551  PKRMDDFQLKGIVEEKFVKWECNSSSATEKNSIAEENKAKADQPKDDTKK   600
 601  TETDNQSNAMKEKHGKSPLALETPNRVSLGQLWLELLKFYTLDFALEEYV   650
 651  ICVRIQDILTRENKNWPKRRIAIEDPFSVKRNVARSLNSQLVYEYVVERF   700
 701  RAAYRYFACPQTKGGNKSTVDFKKREKGKISNKKPVKSNNMATNGCILLG   750
 751  ETTEKINAEREQPVQCDEMDCTSQRCIIDNNNLLVNELDFADHGQDSSSL   800
 801  STSKSSEIEPKLDKKQDDLAPSETCLKKELSQCNCIDLSKSPDPDKSTGT   850
 851  DCRSNLETESSHQSVCTDTSATSCNCKATEDASDLNDDDNLPTQELYYVF   900
 901  DKFILTSGKPPTIVCSICKKDGHSKNDCPEDFRKIDLKPLPPMTNRFREI   950
 951  LDLVCKRCFDELSPPCSEQHNREQILIGLEKFIQKEYDEKARLCLFGSSK  1000
1001  NGFGFRDSDLDICMTLEGHENAEKLNCKEIIENLAKILKRHPGLRNILPI  1050
1051  TTAKVPIVKFEHRRSGLEGDISLYNTLAQHNTRMLATYAAIDPRVQYLGY  1100
1101  TMKVFAKRCDIGDASRGSLSSYAYILMVLYFLQQRKPPVIPVLQEIFDGK  1150
1151  QIPQRMVDGWNAFFFDKTEELKKRLPSLGKNTESLGELWLGLLRFYTEEF  1200
1201  DFKEYVISIRQKKLLTTFEKQWTSKCIAIEDPFDLNHNLGAGVSRKMTNF  1250
1251  IMKAFINGRKLFGTPFYPLIGREAEYFFDSRVLTDGELAPNDRCCRVCGK  1300
1301  IGHYMKDCPKRKSLLFRLKKKDSEEEKEGNEEEKDSRDVLDPRDLHDTRD  1350
1351  FRDPRDLRCFICGDAGHVRRECPEVKLARQRNSSVAAAQLVRNLVNAQQV  1400
1401  AGSAQQQGDQSIRTRQSSECSESPSYSPQPQPFPQNSSQSAAITQPSSQP  1450
1451  GSQPKLGPPQQGAQPPHQVQMPLYNFPQSPPAQYSPMHNMGLLPMHPLQI  1500
1501  PAPSWPIHGPVIHSAPGSAPSNIGLNDPSIIFAQPAARPVAIPNTSHDGH  1550
1551  WPRTVAPNSLVNSGAVGNSEPGFRGLTPPIPWEHAPRPHFPLVPASWPYG  1600
1601  LHQNFMHQGNARFQPNKPFYTQDRCATRRCRERCPHPPRGNVSE        1644

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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