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

NucPred

Fetching O81016 from www.uniprot.org...

The NucPred score for your sequence is 0.44 (see score help below)

   1  MWNSAENAFSRSTSFKDEIEDEEELRWAALQRLPTYSRIRRGIFRDMVGE    50
  51  PKEIQIGNLEASEQRLLLDRLVNSVENDPEQFFARVRKRFDAVDLKFPKI   100
 101  EVRFQNLMVESFVHVGSRALPTIPNFIINMAEGLLRNIHVIGGKRNKLTI   150
 151  LDGISGVIRPSRLTLLLGPPSSGKTTLLLALAGRLGTNLQTSGKITYNGY   200
 201  DLKEIIAPRTSAYVSQQDWHVAEMTVRQTLEFAGRCQGVGFKYDMLLELA   250
 251  RREKLAGIVPDEDLDIFMKSLALGGMETSLVVEYVMKILGLDTCADTLVG   300
 301  DEMIKGISGGQKKRLTTGELLVGPARVLFMDEISNGLDSSTTHQIIMYMR   350
 351  HSTHALEGTTVISLLQPSPETYELFDDVILMSEGQIIYQGPRDEVLDFFS   400
 401  SLGFTCPDRKNVADFLQEVTSKKDQQQYWSVPFRPYRYVPPGKFAEAFRS   450
 451  YPTGKKLAKKLEVPFDKRFNHSAALSTSQYGVKKSELLKINFAWQKQLMK   500
 501  QNAFIYVFKFVQLLLVALITMTVFCRTTMHHNTIDDGNIYLGSLYFSMVI   550
 551  ILFNGFTEVPMLVAKLPVLYKHRDLHFYPSWAYTLPSWLLSIPTSIIESA   600
 601  TWVAVTYYTIGYDPLFSRFLQQFLLYFSLHQMSLGLFRVMGSLGRHMIVA   650
 651  NTFGSFAMLVVMTLGGFIISRDSIPSWWIWGYWISPLMYAQNAASVNEFL   700
 701  GHNWQKTAGNHTSDSLGLALLKERSLFSGNYWYWIGVAALLGYTVLFNIL   750
 751  FTLFLAHLNPWGKFQAVVSREELDEREKKRKGDEFVVELREYLQHSGSIH   800
 801  GKYFKNRGMVLPFQPLSLSFSNINYYVDVPLGLKEQGILEDRLQLLVNIT   850
 851  GAFRPGVLTALVGVSGAGKTTLMDVLAGRKTGGTIEGDVYISGFPKRQET   900
 901  FARISGYCEQNDVHSPCLTVVESLLFSACLRLPADIDSETQRAFVHEVME   950
 951  LVELTSLSGALVGLPGVDGLSTEQRKRLTIAVELVANPSIVFMDEPTSGL  1000
1001  DARAAAIVMRTVRNIVNTGRTIVCTIHQPSIDIFESFDELLFMKRGGELI  1050
1051  YAGPLGQKSCELIKYFESIEGVQKIKPGHNPAAWMLDVTASTEEHRLGVD  1100
1101  FAEIYRNSNLCQRNKELIEVLSKPSNIAKEIEFPTRYSQSLYSQFVACLW  1150
1151  KQNLSYWRNPQYTAVRFFYTVVISLMLGTICWKFGSKRDTQQQLFNAMGS  1200
1201  MYAAVLFIGITNATAAQPVVSIERFVSYRERAAGMYSALPFAFAQVFIEF  1250
1251  PYVLAQSTIYSTIFYAMAAFEWSAVKFLWYLFFMYFSIMYFTFYGMMTTA  1300
1301  ITPNHNVASIIAAPFYMLWNLFSGFMIPYKRIPLWWRWYYWANPVAWTLY  1350
1351  GLLVSQYGDDERSVKLSDGIHQVMVKQLLEDVMGYKHDFLGVSAIMVVAF  1400
1401  CVFFSLVFAFAIKAFNFQRR                                1420

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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