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

NucPred

Fetching Q00685 from www.uniprot.org...

The NucPred score for your sequence is 0.58 (see score help below)

   1  VLLLMSVGTSVTQDPMVLLSVPSVILIGSDVNVLVDHAASTEDVSVVVRA    50
  51  EEFLTKKQLATQTITLTQLDPAIATLKLGFDIENPDKTNSASTKHHVRLV   100
 101  AKVESKSFNKEITAHALLSYRSGHVVVQTDKPIYTPDEKVKYRMFPMNRE   150
 151  DVHRIPVRQSMTVDIVNADGVIVERQIKTIKATDEGIVDGTSFTIPAISK   200
 201  HGTWKIFARMSGAPNINSSAEFDVREYILPTFEVKINPKQRVFHINDEEF   250
 251  VVDITANYFNQELVSGTAYVRYFLENGDVPKLVDSSSTTLVAGEGLSILK   300
 301  KEKLLKLFPNAKDLLAFSLTIKTTVLSSQAAETEEAELVGIKIVESRYQI   350
 351  TATKTSRYFKPELPYFIQVEVRNADGSPSKEVDVVAKVQVGSATINPQKM   400
 401  RTDSNGLTSFTVTPPNVNQLTVTVRTDERHPSNEQGELVYTAQKYASASY   450
 451  MHIDVTRIMRLGETLNVFLTAKTTQLNAVTHFTYMVLTRGVIVKTNRKTK   500
 501  ESGGGPSNVRIPITPDMAPRFRFLAYYILPGGEIVADSVTVEVTELCKSQ   550
 551  VSLSLKGRPTLEPKAMLTLDLIGEPDARVGLLAVDQAVYAVNRKHRLTQD   600
 601  RVWKAMETFDTGCTAEGGAGRPGVFSDAGLALITSKGLNTTDRSEIGCPK   650
 651  VPSRKPRQLSMLQIRREAEKYTQEFRKCCVDGLKMSPTGQGCEERLKRVT   700
 701  GPKECVDAFLQCCKKAEEYRKSESLGAKTVLRRNDFMELDLMNEDEVNMM   750
 751  AYFPQSWGWNKYKNSCKYGRHPQIRLQLPDTITTWNMQAVSISKTRGVCL   800
 801  ADPLLLVSTKDFFIKLHLPYSVKRGEQTEIRVILYNYMEESLTILTEMDI   850
 851  VESICSTSKSGAKPSQKSTVKGKGAMVVSFPIVPLKIGEHHISIRSRVYG   900
 901  RTFGDGVQKILRVAPEGVRDIRSESRSVHVEERETFFIKNEISPDVVPNS   950
 951  DVLTFISVKGDELAETMVNCLDAKSISNLIQIPTGCGEQNMIKMAPTTLT  1000
1001  LIYLDSVQEWEKIGLHRREEAIGFLKQGYSRELSYRKADHSYAAFIKRPS  1050
1051  STWLTAFVVKVYSLAKRVIIVDNQELCGPVEWIIKNRQNSDGSYREDGPV  1100
1101  IHREMQGGVGGTEGHVSMTAFILIGIQQAQEYCGVSVPNYKQSMNRAVQF  1150
1151  LASKVSDLKRMYTIAITRYALALQDPESEAAHSSWKKLENRTTFESKGHR  1200
1201  YWKAEETSHVLRMSAISVEATAYGLLTYLRKKDYESAREIVDWLTEQRNY  1250
1251  GGGFQSTQDTILALQAMAQYKMDSSSKELIDVQLEITSPKNNFEKKMKIT  1300
1301  EETRFVQEPHKIPPGGNITIKASGRGTFTLSIMSVFNKVAPSSKSCSTFD  1350
1351  LKVTMTEADDGESPQGRLGWFDGKRRRRRDIGDEGGVEAVYRMNMCTRYK  1400
1401  PRKEDLSSESGMTIIEVNMLTGFIPDKNDLIQLKESVDKYISNYEITDSV  1450
1451  LIIYWDKVPSTEDYCFAFKIKQMLRSDMIQPVTASVYDYYSPADKCTRLY  1500
1501  NLPGGYVELSPLCQNDLCQCVEVSCPAKKPKFDTSITVLHRQEAACVAGI  1550
1551  DYAYVGIVDNRTEVGSFVYYTVNIQTVIKSGQDQAIQPKATRLFIVTRSC  1600
1601  DGRLGMETPRQYLLMGRKGETKDRNDRFQYVLDASSWVEQWPVDEKCNQP  1650
1651  NVQTFCAIKREYEFSMQIQGCSS                             1673

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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