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

NucPred

Fetching Q10570 from www.uniprot.org...

The NucPred score for your sequence is 0.39 (see score help below)

   1  MYAVYKQAHPPTGLEFSMYCNFFNNSERNLVVAGTSQLYVYRLNRDAEAL    50
  51  TKNDRSTEGKAHREKLELAASFSFFGNVMSMASVQLAGAKRDALLLSFKD   100
 101  AKLSVVEYDPGTHDLKTLSLHYFEEPELRDGFVQNVHTPRVRVDPDGRCA   150
 151  AMLVYGTRLVVLPFRRESLAEEHEGLVGEGQRSSFLPSYIIDVRALDEKL   200
 201  LNIIDLQFLHGYYEPTLLILFEPNQTWPGRVAVRQDTCSIVAISLNITQK   250
 251  VHPVIWSLTSLPFDCTQALAVPKPIGGVVVFAVNSLLYLNQSVPPYGVAL   300
 301  NSLTTGTTAFPLRTQEGVRITLDCAQATFISYDKMVISLKGGEIYVLTLI   350
 351  TDGMRSVRAFHFDKAAASVLTTSMVTMEPGYLFLGSRLGNSLLLKYTEKL   400
 401  QEPPASAVREAADKEEPPSKKKRVDATAGWSAAGKSVPQDEVDEIEVYGS   450
 451  EAQSGTQLATYSFEVCDSILNIGPCANAAVGEPAFLSEEFQNSPEPDLEI   500
 501  VVCSGHGKNGALSVLQKSIRPQVVTTFELPGCYDMWTVIAPVRKEEEDNP   550
 551  KGEGTEQEPSTTPEADDDGRRHGFLILSREDSTMILQTGQEIMELDTSGF   600
 601  ATQGPTVFAGNIGDNRYIVQVSPLGIRLLEGVNQLHFIPVDLGAPIVQCA   650
 651  VADPYVVIMSAEGHVTMFLLKSDSYGGRHHRLALHKPPLHHQSKVITLCL   700
 701  YRDLSGMFTTESRLGGARDELGGRSGPEAEGLGSETSPTVDDEEEMLYGD   750
 751  SGSLFSPSKEEARRSSQPPADRDPAPFRAEPTHWCLLVRENGTMEIYQLP   800
 801  DWRLVFLVKNFPVGQRVLVDSSFGQPTTQGEARREEATRQGELPLVKEVL   850
 851  LVALGSRQSRPYLLVHVDQELLIYEAFPHDSQLGQGNLKVRFKKVPHNIN   900
 901  FREKKPKPSKKKAEGGGAEEGAGARGRVARFRYFEDIYGYSGVFICGPSP   950
 951  HWLLVTGRGALRLHPMAIDGPVDSFAPFHNVNCPRGFLYFNRQGELRISV  1000
1001  LPAYLSYDAPWPVRKIPLRCTAHYVAYHVESKVYAVATSTNTPCARIPRM  1050
1051  TGEEKEFETIERDERYIHPQQEAFSIQLISPVSWEAIPNARIELQEWEHV  1100
1101  TCMKTVSLRSEETVSGLKGYVAAGTCLMQGEEVTCRGRILIMDVIEVVPE  1150
1151  PGQPLTKNKFKVLYEKEQKGPVTALCHCNGHLVSAIGQKIFLWSLRASEL  1200
1201  TGMAFIDTQLYIHQMISVKNFILAADVMKSISLLRYQEESKTLSLVSRDA  1250
1251  KPLEVYSVDFMVDNAQLGFLVSDRDRNLMVYMYLPEAKESFGGMRLLRRA  1300
1301  DFHVGAHVNTFWRTPCRGATEGLSKKSVVWENKHITWFATLDGGIGLLLP  1350
1351  MQEKTYRRLLMLQNALTTMLPHHAGLNPRAFRMLHVDRRTLQNAVRNVLD  1400
1401  GELLNRYLYLSTMERSELAKKIGTTPDIILDDLLETDRVTAHF         1443

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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