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

NucPred

Fetching Q14160 from www.uniprot.org...

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

   1  MLKCIPLWRCNRHVESVDKRHCSLQAVPEEIYRYSRSLEELLLDANQLRE    50
  51  LPKPFFRLLNLRKLGLSDNEIQRLPPEVANFMQLVELDVSRNDIPEIPES   100
 101  IKFCKALEIADFSGNPLSRLPDGFTQLRSLAHLALNDVSLQALPGDVGNL   150
 151  ANLVTLELRENLLKSLPASLSFLVKLEQLDLGGNDLEVLPDTLGALPNLR   200
 201  ELWLDRNQLSALPPELGNLRRLVCLDVSENRLEELPAELGGLVLLTDLLL   250
 251  SQNLLRRLPDGIGQLKQLSILKVDQNRLCEVTEAIGDCENLSELILTENL   300
 301  LMALPRSLGKLTKLTNLNVDRNHLEALPPEIGGCVALSVLSLRDNRLAVL   350
 351  PPELAHTTELHVLDVAGNRLQSLPFALTHLNLKALWLAENQAQPMLRFQT   400
 401  EDDARTGEKVLTCYLLPQQPPPSLEDAGQQGSLSETWSDAPPSRVSVIQF   450
 451  LEAPIGDEDAEEAAAEKRGLQRRATPHPSELKVMKRSIEGRRSEACPCQP   500
 501  DSGSPLPAEEEKRLSAESGLSEDSRPSASTVSEAEPEGPSAEAQGGSQQE   550
 551  ATTAGGEEDAEEDYQEPTVHFAEDALLPGDDREIEEGQPEAPWTLPGGRQ   600
 601  RLIRKDTPHYKKHFKISKLPQPEAVVALLQGMQPDGEGPVAPGGWHNGPH   650
 651  APWAPRAQKEEEEEEEGSPQEEEEEEEEENRAEEEEASTEEEDKEGAVVS   700
 701  APSVKGVSFDQANNLLIEPARIEEEELTLTILRQTGGLGISIAGGKGSTP   750
 751  YKGDDEGIFISRVSEEGPAARAGVRVGDKLLEVNGVALQGAEHHEAVEAL   800
 801  RGAGTAVQMRVWRERMVEPENAVTITPLRPEDDYSPRERRGGGLRLPLLP   850
 851  PESPGPLRQRHVACLARSERGLGFSIAGGKGSTPYRAGDAGIFVSRIAEG   900
 901  GAAHRAGTLQVGDRVLSINGVDVTEARHDHAVSLLTAASPTIALLLEREA   950
 951  GGPLPPSPLPHSSPPTAAVATTSITTATPGVPGLPSLAPSLLAAALEGPY  1000
1001  PVEEIRLPRAGGPLGLSIVGGSDHSSHPFGVQEPGVFISKVLPRGLAARS  1050
1051  GLRVGDRILAVNGQDVRDATHQEAVSALLRPCLELSLLVRRDPAPPGLRE  1100
1101  LCIQKAPGERLGISIRGGARGHAGNPRDPTDEGIFISKVSPTGAAGRDGR  1150
1151  LRVGLRLLEVNQQSLLGLTHGEAVQLLRSVGDTLTVLVCDGFEASTDAAL  1200
1201  EVSPGVIANPFAAGIGHRNSLESISSIDRELSPEGPGKEKELPGQTLHWG  1250
1251  PEATEAAGRGLQPLKLDYRALAAVPSAGSVQRVPSGAAGGKMAESPCSPS  1300
1301  GQQPPSPPSPDELPANVKQAYRAFAAVPTSHPPEDAPAQPPTPGPAASPE  1350
1351  QLSFRERQKYFELEVRVPQAEGPPKRVSLVGADDLRKMQEEEARKLQQKR  1400
1401  AQMLREAAEAGAEARLALDGETLGEEEQEDEQPPWASPSPTSRQSPASPP  1450
1451  PLGGGAPVRTAKAERRHQERLRVQSPEPPAPERALSPAELRALEAEKRAL  1500
1501  WRAARMKSLEQDALRAQMVLSRSQEGRGTRGPLERLAEAPSPAPTPSPTP  1550
1551  VEDLGPQTSTSPGRLPLSGKKFDYRAFAALPSSRPVYDIQSPDFAEELRS  1600
1601  LEPSPSPGPQEEDGEVALVLLGRPSPGAVGPEDVALCSSRRPVRPGRRGL  1650
1651  GPVPS                                               1655

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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