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

NucPred

Fetching P02468 from www.uniprot.org...

The NucPred score for your sequence is 0.62 (see score help below)

   1  MTGGGRAALALQPRGRLWPLLAVLAAVAGCVRAAMDECADEGGRPQRCMP    50
  51  EFVNAAFNVTVVATNTCGTPPEEYCVQTGVTGVTKSCHLCDAGQQHLQHG   100
 101  AAFLTDYNNQADTTWWQSQTMLAGVQYPNSINLTLHLGKAFDITYVRLKF   150
 151  HTSRPESFAIYKRTREDGPWIPYQYYSGSCENTYSKANRGFIRTGGDEQQ   200
 201  ALCTDEFSDISPLTGGNVAFSTLEGRPSAYNFDNSPVLQEWVTATDIRVT   250
 251  LNRLNTFGDEVFNEPKVLKSYYYAISDFAVGGRCKCNGHASECVKNEFDK   300
 301  LMCNCKHNTYGVDCEKCLPFFNDRPWRRATAESASESLPCDCNGRSQECY   350
 351  FDPELYRSTGHGGHCTNCRDNTDGAKCERCRENFFRLGNTEACSPCHCSP   400
 401  VGSLSTQCDSYGRCSCKPGVMGDKCDRCQPGFHSLTEAGCRPCSCDLRGS   450
 451  TDECNVETGRCVCKDNVEGFNCERCKPGFFNLESSNPKGCTPCFCFGHSS   500
 501  VCTNAVGYSVYDISSTFQIDEDGWRVEQRDGSEASLEWSSDRQDIAVISD   550
 551  SYFPRYFIAPVKFLGNQVLSYGQNLSFSFRVDRRDTRLSAEDLVLEGAGL   600
 601  RVSVPLIAQGNSYPSETTVKYIFRLHEATDYPWRPALSPFEFQKLLNNLT   650
 651  SIKIRGTYSERTAGYLDDVTLQSARPGPGVPATWVESCTCPVGYGGQFCE   700
 701  TCLPGYRRETPSLGPYSPCVLCTCNGHSETCDPETGVCDCRDNTAGPHCE   750
 751  KCSDGYYGDSTLGTSSDCQPCPCPGGSSCAIVPKTKEVVCTHCPTGTAGK   800
 801  RCELCDDGYFGDPLGSNGPVRLCRPCQCNDNIDPNAVGNCNRLTGECLKC   850
 851  IYNTAGFYCDRCKEGFFGNPLAPNPADKCKACACNPYGTVQQQSSCNPVT   900
 901  GQCQCLPHVSGRDCGTCDPGYYNLQSGQGCERCDCHALGSTNGQCDIRTG   950
 951  QCECQPGITGQHCERCETNHFGFGPEGCKPCDCHHEGSLSLQCKDDGRCE  1000
1001  CREGFVGNRCDQCEENYFYNRSWPGCQECPACYRLVKDKAAEHRVKLQEL  1050
1051  ESLIANLGTGDDMVTDQAFEDRLKEAEREVTDLLREAQEVKDVDQNLMDR  1100
1101  LQRVNSSLHSQISRLQNIRNTIEETGILAERARSRVESTEQLIEIASREL  1150
1151  EKAKMAAANVSITQPESTGEPNNMTLLAEEARRLAERHKQEADDIVRVAK  1200
1201  TANETSAEAYNLLLRTLAGENQTALEIEELNRKYEQAKNISQDLEKQAAR  1250
1251  VHEEAKRAGDKAVEIYASVAQLTPVDSEALENEANKIKKEAADLDRLIDQ  1300
1301  KLKDYEDLREDMRGKEHEVKNLLEKGKAEQQTADQLLARADAAKALAEEA  1350
1351  AKKGRSTLQEANDILNNLKDFDRRVNDNKTAAEEALRRIPAINRTIAEAN  1400
1401  EKTREAQLALGNAAADATEAKNKAHEAERIASAVQKNATSTKADAERTFG  1450
1451  EVTDLDNEVNGMLRQLEEAENELKRKQDDADQDMMMAGMASQAAQEAELN  1500
1501  ARKAKNSVSSLLSQLNNLLDQLGQLDTVDLNKLNEIEGSLNKAKDEMKAS  1550
1551  DLDRKVSDLESEARKQEAAIMDYNRDIAEIIKDIHNLEDIKKTLPTGCFN  1600
1601  TPSIEKP                                             1607

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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