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

NucPred

Fetching Q9Y4G8 from www.uniprot.org...

The NucPred score for your sequence is 0.98 (see score help below)

   1  MKPLAIPANHGVMGQQEKHSLPADFTKLHLTDSLHPQVTHVSSSHSGCSI    50
51 TSDSGSSSLSDIYQATESEAGDMDLSGLPETAVDSEDDDDEEDIERASDP 100
101 LMSRDIVRDCLEKDPIDRTDDDIEQLLEFMHQLPAFANMTMSVRRELCAV 150
151 MVFAVVERAGTIVLNDGEELDSWSVILNGSVEVTYPDGKAEILCMGNSFG 200
201 VSPTMDKEYMKGVMRTKVDDCQFVCIAQQDYCRILNQVEKNMQKVEEEGE 250
251 IVMVKEHRELDRTGTRKGHIVIKGTSERLTMHLVEEHSVVDPTFIEDFLL 300
301 TYRTFLSSPMEVGKKLLEWFNDPSLRDKVTRVVLLWVNNHFNDFEGDPAM 350
351 TRFLEEFENNLEREKMGGHLRLLNIACAAKAKRRLMTLTKPSREAPLPFI 400
401 LLGGSEKGFGIFVDSVDSGSKATEAGLKRGDQILEVNGQNFENIQLSKAM 450
451 EILRNNTHLSITVKTNLFVFKELLTRLSEEKRNGAPHLPKIGDIKKASRY 500
501 SIPDLAVDVEQVIGLEKVNKKSKANTVGGRNKLKKILDKTRISILPQKPY 550
551 NDIGIGQSQDDSIVGLRQTKHIPTALPVSGTLSSSNPDLLQSHHRILDFS 600
601 ATPDLPDQVLRVFKADQQSRYIMISKDTTAKEVVIQAIREFAVTATPDQY 650
651 SLCEVSVTPEGVIKQRRLPDQLSKLADRIQLSGRYYLKNNMETETLCSDE 700
701 DAQELLRESQISLLQLSTVEVATQLSMRNFELFRNIEPTEYIDDLFKLRS 750
751 KTSCANLKRFEEVINQETFWVASEILRETNQLKRMKIIKHFIKIALHCRE 800
801 CKNFNSMFAIISGLNLAPVARLRTTWEKLPNKYEKLFQDLQDLFDPSRNM 850
851 AKYRNVLNSQNLQPPIIPLFPVIKKDLTFLHEGNDSKVDGLVNFEKLRMI 900
901 AKEIRHVGRMASVNMDPALMFRTRKKKWRSLGSLSQGSTNATVLDVAQTG 950
951 GHKKRVRRSSFLNAKKLYEDAQMARKVKQYLSNLELEMDEESLQTLSLQC 1000
1001 EPATNTLPKNPGDKKPVKSETSPVAPRAGSQQKAQSLPQPQQQPPPAHKI 1050
1051 NQGLQVPAVSLYPSRKKVPVKDLPPFGINSPQALKKILSLSEEGSLERHK 1100
1101 KQAEDTISNASSQLSSPPTSPQSSPRKGYTLAPSGTVDNFSDSGHSEISS 1150
1151 RSSIVSNSSFDSVPVSLHDERRQRHSVSIVETNLGMGRMERRTMIEPDQY 1200
1201 SLGSYAPMSEGRGLYATATVISSPSTEELSQDQGDRASLDAADSGRGSWT 1250
1251 SCSSGSHDNIQTIQHQRSWETLPFGHTHFDYSGDPAGLWASSSHMDQIMF 1300
1301 SDHSTKYNRQNQSRESLEQAQSRASWASSTGYWGEDSEGDTGTIKRRGGK 1350
1351 DVSIEAESSSLTSVTTEETKPVPMPAHIAVASSTTKGLIARKEGRYREPP 1400
1401 PTPPGYIGIPITDFPEGHSHPARKPPDYNVALQRSRMVARSSDTAGPSSV 1450
1451 QQPHGHPTSSRPVNKPQWHKPNESDPRLAPYQSQGFSTEEDEDEQVSAV 1499

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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