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

NucPred

Fetching Q00681 from www.uniprot.org...

The NucPred score for your sequence is 0.63 (see score help below)

   1  MTQKTIQQVPRQGLELLASTQDLAQLCYIYGEPAEGEDSTADESIINTPQ    50
  51  CSTIPEVAVEPEVQPIPDTPLTAIFIIRALVARKLRRSETEIDPSRSIKE   100
 101  LCGGKSTLQNELIGELGNEFQTSLPDRAEDVSLADLDAALGEVSLGPTSV   150
 151  SLLQRVFTAKMPARMTVSNVRERLAEIWGLGFHRQTAVLVAALAAEPHSR   200
 201  LTSLEAAYQYWDGLTEAYGQSLGLFLRKAISQQAARSDDQGAQAIAPADS   250
 251  LGSKDLARKQYEALREYLGIRTPTTKQDGLDLADLQQKLDCWTAEFSDDF   300
 301  LSQISRRFDARKTRWYRDWWNSARQELLTICQNSNVQWTDKMREHFVQRA   350
 351  EEGLVEIARAHSLAKPLVPDLIQAISLPPVVRLGRLATMMPRTVVTLKGE   400
 401  IQCEEHEREPSCFVEFFSSWIQANNIRCTIQSNGEDLTSVFINSLVHASQ   450
 451  QGVSFANHTYLITGAGPGSIGQHIVRRLLTGGARVIVTTSREPLPAAAFF   500
 501  KELYSKCGNRGSQLHLVPFNQASVVDCERLIGYIYDDLGLDLDAILPFAA   550
 551  TSQVGAEIDGLDASNEAAFRLMLVNVLRLVGFVVSQKRRRGISCRPTQVV   600
 601  LPLSPNHGILGGDGLYAESKRGLETLIQRFHSESWKEELSICGVSIGWTR   650
 651  STGLMAANDLVAETAEKQGRVLTFSVDEMGDLISLLLTPQLATRCEDAPV   700
 701  MADFSGNLSCWRDASAQLAAARASLRERADTARALAQEDEREYRCRRAGS   750
 751  TQEPVDQRVSLHLGFPSLPEYDPLLHPDLVPADAVVVVGFAELGPWGSAR   800
 801  IRWEMESRGCLSPAGYVETAWLMNLIRHVDNVNYVGWVDGEDGKPVADAD   850
 851  IPKRYGERILSNAGIRSLPSDNREVFQEIVLEQDLPSFETTRENAEALQQ   900
 901  RHGDMVQVSTLKNGLCLVQLQHGATIRVPKSIMSPPGVAGQLPTGWSPER   950
 951  YGIPAEIVQQVDPVALVLLCCVAEAFYSAGISDPMEIFEHIHLSELGNFV  1000
1001  GSSMGGVVNTRALYHDVCLDKDVQSDALQETYLNTAPAWVNMLYLGAAGP  1050
1051  IKTPVGACATALESVDSAVESIKAGQTKICLVGGYDDLQPEESAGFARMK  1100
1101  ATVSVRDEQARGREPGEMSRPTAASRSGFVESQGCGVQLLCRGDVALAMG  1150
1151  LPIYGIIAGTGMASDGIGRSVPAPGQGILTFAQEDAQNPAPIRTALARWG  1200
1201  LGIDDITVASLHATSTPANDTNEPLVIQREMTHLGRTSGRPLWAICQKFV  1250
1251  TGHPKAPAAAWMLNGCLQVLDTGLVPGNRNADDVDPALRSFSHLCFPIRS  1300
1301  IQTDGIKAFLLNSCGFGQKEAQLVGVHPRYFLGLLSEPEFEEYRTRRQLR  1350
1351  IAGAERAYISAMMTNSIVCVQSHPPFGPAEMHSILLDPSARICLDSSTNS  1400
1401  YRVTKASTPVYTGFQRPHDKREDPRPSTIGVDTVTLSSFNAHENAIFLQR  1450
1451  NYTERERQSLQLQSHRSFRSAVASGWCAKEAVFKCLQTVSKGAGAAMSEI  1500
1501  EIVRVQGAPSVLHGDALAAAQKAGLDNIQLSLSYGDDCVVAVALGVRKWC  1550
1551  LWPLASIIR                                           1559

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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