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

NucPred

Fetching Q2U561 from www.uniprot.org...

The NucPred score for your sequence is 0.82 (see score help below)

   1  MSARDLVEGEAMLDDEENEEELADDYDGEGEAHQGAGTANPYDSSEEDDD    50
  51  DDDDEEAARAVREGFIVDEDEELEDRAERRREKRKRRREEREREDEHLDE   100
 101  EDLELIGELNPSLQAPVAAESKFKRLKRGHKDRDLRQPSQGIDDIFNSDE   150
 151  EEEAAGDYGRHGHRRHMHDEMDDFIEEDVFSDEELQREREDLEIARPAKK   200
 201  GMTGLGATDAAGLDENALEDMRAAFGDGNEYLFALEMEDQEEEQEEDEEK   250
 251  HLDLKDVFEPSQLAEKMLTEEDNQIRLLDEPERHQIARKPYRNVVLTEEQ   300
 301  FREEAAWISNLMLLKKRIEPELREPFQRSVAKVLEFLVTDDWEVPFIFQH   350
 351  RKDYMIHAVKAPVEGAGEDGDASQYTVRAEKLLNMTDLWDIFDHDLKFKA   400
 401  LVEKRNTIQKTYDNLQSLFNVSDSVVEEMLPAAVTMEELQDVQDYIHFQY   450
 451  ASQLRDMTLMNSDVNGETHRRKASSKTFFERVRNGKAYGLVRAFGITADA   500
 501  FAQNALKEGRRQYTEDPAERPEEMADGFVDNDFSNASHVIKAAKSLFAEE   550
 551  IVMSPKMRKVIRQAYYMNGAVDCFRTEKGLRRIDEQHPYYEFKYLRNQQL   600
 601  SDIARRPELYLRMLKAEEEGLVEVKVRFENFDQFRQRLYPDIESDNYSEI   650
 651  ADGWNRSRRDVLDMALGKLERLINRSVKENIRQECENHVAKECRETFSQR   700
 701  LDQAPYKPKGMVLGTVPRVLALSTGSGVVGREPIHWAYIEEDGRVLENGK   750
 751  FVDLSIGDRDRNIPDGKDVEAFVELVDRRRPDVIGVSGMSPETRRLYKLL   800
 801  AEVVDKKDLRGAPYTDDHDEEISDRLEVIIVNDEVARLYQHSERAKKDHP   850
 851  SFAPLTHYCVALAKYLQSPLKEYASLGRDIVSIQFKPGQQLVTQELLLKQ   900
 901  LETALVDMVNLVGVDINEAVTDSSTANLLPYVCGLGPRKAAHLLKIVNMN   950
 951  GGVVNNRVELLGVNAQYPAMGVKVWNNCASFLYIDFENVDPDADPLDNTR  1000
1001  VHPEDYDIARKMAADALELDEEDIKAETDENGTGAIVRKLFREEAQDRVN  1050
1051  DLILEEYAEQLEKNLNQRKRATLETIRAELQQPYEELRKQYVFLSTDDIF  1100
1101  TMLTGETSDTLAEGMVVPISIKRVSDDHIDGKLDCGIDALVPESELTDRY  1150
1151  DIPVRALYSPHQTVSAKILFLNRKNFTCNVSLREEQVSRPVSNTQDRLRG  1200
1201  EWDERQEQQDRESLQEKTQSGGRTMRVIKHPLFRPFNSTQAEEFLGSQSR  1250
1251  GDVVIRPSSKGHDHLAVTWKVADGIFQHIDVLELDKENEFSVGRTLKVGG  1300
1301  RYTYSDLDDLIFNHVKAMAKKVDEMMLHEKYQDGTKDATYSWLETYTKAN  1350
1351  PKRSAYAFCIDPKHAGYFFLCFKAGENARLHSWPVKVIPQGYELQRNPYP  1400
1401  DMRALCNGFKLLFTNMQAGKRR                              1422

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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