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

NucPred

Fetching Q26627 from www.uniprot.org...

The NucPred score for your sequence is 0.10 (see score help below)

   1  MSVFVILILFNAILNFKTVGPAAVSSKTVDCASAPCMNGGTCADGFNNFT    50
  51  CFCEEGFTGSMCETEYGCFRPWFYGPAFGYCYLWERVDYNWTQARESCID   100
 101  QGRGAELASIHSAEENAFVYAQIRRYAWIGLSDQVTEGVFDYADGTPVDY   150
 151  LSFPDKNKQSETRDCVYVKHLRVDNWSLLDCRANKTSICKSTTTFSATDG   200
 201  CATGWVHNPATGYCYFYEERGGMWSKGREFCLDAGADLASIHSAEENAFI   250
 251  FDMLTEFVWLGLNDLETEGVYTNFSDGTPADFDNFPADNYQNEDHDCVSI   300
 301  RHLEKTDRYWFFLGCDDTVTSICKRPHEVVATQAPPYLFTTTDVPATTTT   350
 351  IPTTTTTISATTRTIDAMILIELLLFPNNVSSIDNIFRVNNTILVTASVL   400
 401  GSFQALSSQILWSITNHLSGDSVQYTVYSEDAVLVRFTTVSIFTIKATAV   450
 451  GNSHNLTATANATVKHVCISSLTTSVKEHCDAPHPAVYLRAFDIHISTHM   500
 501  ELNGKCIDPMTPDFKWRIFTSTEADDVVTAFEKITHTRQVMIPRGTLPYG   550
 551  IYSLNLNAKTRLKTSGEVTGEKEIISWLEIQPPPLVAVIKGGASRSHGVS   600
 601  SNLIVDGSNSYDPDVPPGSSSNVTFLWYCVVVDPDVMYSSLDEAIQNTDN   650
 651  ACFEDEGIMMNSTSSMIEVIANKLNANVTMNFWLNISKEGQISGLTQQRI   700
 701  HLTLGLLPEIEISCISNCNMYIFTAERLVLHASCTNCDSENEDVSFRWSL   750
 751  ESNHTSVIGDLSSQTTTGLDQPYLVLKPLTFDSISEMGSIILRVTGSQSD   800
 801  SDGYAEFSVDLPHNAPPALGSCVVTPDEGYALQTDFTVTCSNFTDVDEPL   850
 851  TYQIILFSHVDVVDWMFVGRGEGFQLYEGSAPIKDGLYLPVGVGTDDHDI   900
 901  LLQVNVRDCNMASTSVYISATVHPPTLDAVGMNLVQELLDMALLVETNVN   950
 951  ALLAVGDPGQAAQLISALGSILNSIGDEDDSEEGRETRSEIRSFLVDCVA  1000
1001  AIPVESMTSLKQSSAALAVVTHNKQEISTHVQMLAASTLSEMTSFVKSKS  1050
1051  GSYTQAQENIESAGTILVEGLSNILSAAKETERLLSDDTSQEREDHKNLI  1100
1101  EVAVSTINDIQDAIVAGKIPSEAATIITSPALSIAVGSISRDELAEATFG  1150
1151  GPEDLGSFRMPSQDVLNQAMEHALGTTVSMKMSAMKWNPFSWPGAGGESI  1200
1201  KSSIVGIQLEADQMLEFHDLTADIDVYLPMRETLSADPVSVHITKTSSDS  1250
1251  VLIDHSSLPVDGALHLTVIAENEPMVALSICTARISITESSCVGTDTPLG  1300
1301  VSNEDPDTDANFTWTVPLVDLKAADGIMIRLYDSEDQPGYENDNITLSVF  1350
1351  MHTLQCNFWNEDQQEWDSTGCKVGPLSKPSTTHCLCNHLTGFFGSSILVP  1400
1401  PNHAQPVIGGHKLTGVDFLICVLIGYGIYCVALVIRVVGCSFAIRVHKVL  1450

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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