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

NucPred

Fetching P14543 from www.uniprot.org...

The NucPred score for your sequence is 0.37 (see score help below)

   1  MLASSSRIRAAWTRALLLPLLLAGPVGCLSRQELFPFGPGQGDLELEDGD    50
  51  DFVSPALELSGALRFYDRSDIDAVYVTTNGIIATSEPPAKESHPGLFPPT   100
 101  FGAVAPFLADLDTTDGLGKVYYREDLSPSITQRAAECVHRGFPEISFQPS   150
 151  SAVVVTWESVAPYQGPSRDPDQKGKRNTFQAVLASSDSSSYAIFLYPEDG   200
 201  LQFHTTFSKKENNQVPAVVAFSQGSVGFLWKSNGAYNIFANDRESVENLA   250
 251  KSSNSGQQGVWVFEIGSPATTNGVVPADVILGTEDGAEYDDEDEDYDLAT   300
 301  TRLGLEDVGTTPFSYKALRRGGADTYSVPSVLSPRRAATERPLGPPTERT   350
 351  RSFQLAVETFHQQHPQVIDVDEVEETGVVFSYNTDSRQTCANNRHQCSVH   400
 401  AECRDYATGFCCSCVAGYTGNGRQCVAEGSPQRVNGKVKGRIFVGSSQVP   450
 451  IVFENTDLHSYVVMNHGRSYTAISTIPETVGYSLLPLAPVGGIIGWMFAV   500
 501  EQDGFKNGFSITGGEFTRQAEVTFVGHPGNLVIKQRFSGIDEHGHLTIDT   550
 551  ELEGRVPQIPFGSSVHIEPYTELYHYSTSVITSSSTREYTVTEPERDGAS   600
 601  PSRIYTYQWRQTITFQECVHDDSRPALPSTQQLSVDSVFVLYNQEEKILR   650
 651  YALSNSIGPVREGSPDALQNPCYIGTHGCDTNAACRPGPRTQFTCECSIG   700
 701  FRGDGRTCYDIDECSEQPSVCGSHTICNNHPGTFRCECVEGYQFSDEGTC   750
 751  VAVVDQRPINYCETGLHNCDIPQRAQCIYTGGSSYTCSCLPGFSGDGQAC   800
 801  QDVDECQPSRCHPDAFCYNTPGSFTCQCKPGYQGDGFRCVPGEVEKTRCQ   850
 851  HEREHILGAAGATDPQRPIPPGLFVPECDAHGHYAPTQCHGSTGYCWCVD   900
 901  RDGREVEGTRTRPGMTPPCLSTVAPPIHQGPAVPTAVIPLPPGTHLLFAQ   950
 951  TGKIERLPLEGNTMRKTEAKAFLHVPAKVIIGLAFDCVDKMVYWTDITEP  1000
1001  SIGRASLHGGEPTTIIRQDLGSPEGIAVDHLGRNIFWTDSNLDRIEVAKL  1050
1051  DGTQRRVLFETDLVNPRGIVTDSVRGNLYWTDWNRDNPKIETSYMDGTNR  1100
1101  RILVQDDLGLPNGLTFDAFSSQLCWVDAGTNRAECLNPSQPSRRKALEGL  1150
1151  QYPFAVTSYGKNLYFTDWKMNSVVALDLAISKETDAFQPHKQTRLYGITT  1200
1201  ALSQCPQGHNYCSVNNGGCTHLCLATPGSRTCRCPDNTLGVDCIEQK     1247

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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