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

NucPred

Fetching Q09884 from www.uniprot.org...

The NucPred score for your sequence is 0.70 (see score help below)

   1  MDISSFLLPQLLRKYQQDVYNIASKQNTLLVMRTGAGKTLLAVKLIKQKL    50
  51  EEQILIQESNLEHKKISVFLVNKVPLVFQQAEYIRSQLPAKVGMFYGELS   100
 101  IEMSEQLLTNIILKYNVIVITADLFYLFLARGFLSINDLNLIIFDECHHA   150
 151  IGNDAYARIMNDFYHRAKAVLSKKHFTLPRIFGMTASPFTGKKGNLYHRL   200
 201  YQWEQLFDSKAHVVSENELADYFCLPEESYVMYSNKLVVPPSDSIIKKCE   250
 251  ETLQGCKLISRAVKTALAETIDMGLWFGEQVWLYLVDFVETKRLKKKALG   300
 301  KQLSDDEELAIDRLKIFVEDWKNNKYSDNGPRIPVFDSTDVTDKVFKLLE   350
 351  LLKATYRKSDSVRTVIFVERKATAFTLSLFMKTLNLPNIRAHSFIGHGPS   400
 401  DQGEFSMTFRRQKDTLHKFKTGKYNVLIATAVAEEGIDVPSCNLVIRFNI   450
 451  CRTVTQYVQSRGRARAMASKFLIFLNTEELLIHERILHEEKNLKFALSEL   500
 501  SNSNIFDSLVCEERERVTDDIVYEVGETGALLTGLYAVSLLYNFCNTLSR   550
 551  DVYTRYYPTFTAQPCLSGWYCFEVELPKACKVPAAQGSPAKSIRKAKQNA   600
 601  AFIMCLDLIRMGLIDKHLKPLDFRRKIADLETLEEDELKDEGYIETYERY   650
 651  VPKSWMKVPEDITRCFVSLLYTDANEGDNHIFHPLVFVQAHSFPKIDSFI   700
 701  LNSTVGPRVKIVLETIEDSFKIDSHLLELLKKSTRYLLQFGLSTSLEQQI   750
 751  PTPYWLAPLNLSCTDYRFLENLIDVDTIQNFFKLPEPVQNVTDLQSDTVL   800
 801  LVNPQSIYEQYAFEGFVNSEFMIPAKKKDKAPSALCKKLPLRLNYSLWGN   850
 851  RAKSIPKSQQVRSFYINDLYILPVSRHLKNSALLIPSILYHIENLLVASS   900
 901  FIEHFRLDCKIDTACQALTSAESQLNFDYDRLEFYGDCFLKLGASITVFL   950
 951  KFPDTQEYQLHFNRKKIISNCNLYKVAIDCELPKYALSTPLEIRHWCPYG  1000
1001  FQKSTSDKCRYAVLQKLSVKRIADMVEASIGACLLDSGLDSALKICKSLS  1050
1051  VGLLDISNWDEWNNYFDLNTYADSLRNVQFPYSSYIEETIGYSFKNKKLL  1100
1101  HLAFIHPSMMSQQGIYENYQQLEFLGDAVLDYIIVQYLYKKYPNATSGEL  1150
1151  TDYKSFYVCNKSLSYIGFVLNLHKYIQHESAAMCDAIFEYQELIEAFRET  1200
1201  ASENPWFWFEIDSPKFISDTLEAMICAIFLDSGFSLQSLQFVLPLFLNSL  1250
1251  GDATHTKAKGDIEHKVYQLLKDQGCEDFGTKCVIEEVKSSHKTLLNTELH  1300
1301  LTKYYGFSFFRHGNIVAYGKSRKVANAKYIMKQRLLKLLEDKSNLLLYSC  1350
1351  NCKFSKKKPSDEQIKGDGKVKSLT                            1374

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.)

Go back to the NucPred Home Page.