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

NucPred

Fetching Q42093 from www.uniprot.org...

The NucPred score for your sequence is 0.28 (see score help below)

   1  MGFEFIEWYCKPVPNGVWTKQVANAFGAYTPCATDSFVLGISQLVLLVLC    50
  51  LYRIWLALKDHKVERFCLRSRLYNYFLALLAAYATAEPLFRLIMGISVLD   100
 101  FDGPGLPPFEAFGLGVKAFAWGAVMVMILMETKIYIRELRWYVRFAVIYA   150
 151  LVGDMVLLNLVLSVKEYYSSYVLYLYTSEVGAQVLFGILLFMHLPNLDTY   200
 201  PGYMPVRSETVDDYEYEEISDGQQICPEKHANIFDKIFFSWMNPLMTLGS   250
 251  KRPLTEKDVWYLDTWDQTETLFTSFQHSWDKELQKPQPWLLRALNNSLGG   300
 301  RFWWGGFWKIGNDCSQFVGPLLLNQLLKSMQEDAPAWMGYIYAFSIFVGV   350
 351  VFGVLCEAQYFQNVMRVGYRLRSALIAAVFRKSLRLTNEGRRKFQTGKIT   400
 401  NLMTTDAESLQQICQSLHTMWSAPFRIIIALILLYQQLGVASLIGALLLV   450
 451  LMFPLQTVIISKMQKLTKEGLQRTDKRIGLMNEVLAAMDTVKCYAWENSF   500
 501  QSKVQTVRDDELSWFRKSQLLGALNMFILNSIPVLVTIVSFGVFTLLGGD   550
 551  LTPARAFTSLSLFAVLRFPLFMLPNIITQVVNANVSLKRLEEVLATEERI   600
 601  LLPNPPIEPGEPAISIRNGYFSWDSKGDRPTLSNINLDVPLGSLVAVVGS   650
 651  TGEGKTSLISAILGELPATSDAIVTLRGSVAYVPQVSWIFNATVRDNILF   700
 701  GSPFDREKYERAIDVTSLKHDLELLPGGDLTEIGERGVNISGGQKQRVSM   750
 751  ARAVYSNSDVYIFDDPLSALDAHVGQQVFEKCIKRELGQKTRVLVTNQLH   800
 801  FLSQVDRIVLVHEGTVKEEGTYEELSSNGPLFQRLMENAGKVEEYSEENG   850
 851  EAEADQTAEQPVANGNTNGLQMDGSDDKKSKEGNKKGGKSVLIKQEERET   900
 901  GVVSWRVLKRYQDALGGAWVVMMLLLCYVLTEVFRVTSSTWLSEWTDAGT   950
 951  PKSHGPLFYNLIYALLSFGQVLVTLTNSYWLIMSSLYAAKKLHDNMLHSI  1000
1001  LRAPMSFFHTNPLGRIINRFAKDLGDIDRTVAVFVNMFMGQVSQLLSTVV  1050
1051  LIGIVSTLSLWAIMPLLVLFYGAYLYYQNTAREVKRMDSISRSPVYAQFG  1100
1101  EALNGLSTIRAYKAYDRMADINGRSMDNNIRFTLVNMGANRWLGIRLETL  1150
1151  GGLMIWLTASFAVMQNGRAENQQAFASTMGLLLSYALNITSLLTGVLRLA  1200
1201  SLAENSLNAVERVGNYIEIPPEAPPVIENNRPPPGWPSSGSIKFEDVVLR  1250
1251  YRPQLPPVLHGVSFFIHPTDKVGIVGRTGAGKSSLLNALFRIVEVEKGRI  1300
1301  LIDDCDVGKFGLMDLRKVLGIIPQSPVLFSGTVRFNLDPFGEHNDADLWE  1350
1351  SLERAHLKDTIRRNPLGLDAEVSEAGENFSVGQRQLLSLSRALLRRSKIL  1400
1401  VLDEATAAVDVRTDALIQKTIREEFKSCTMLIIAHRLNTIIDCDKILVLD  1450
1451  SGRVQEFSSPENLLSNEGSSFSKMVQSTGAANAEYLRSLVLDNKRAKDDS  1500
1501  HHLQGQRKWLASSRWAAAAQFALAASLTSSHNDLQSLEIEDDSSILKRTN  1550
1551  DAVVTLRSVLEGKHDKEIAESLEEHNISREGWLSSLYRMVEGLAVMSRLA  1600
1601  RNRMQQPDYNFEGNTFDWDNVEM                             1623

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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