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

NucPred

Fetching Q00959 from www.uniprot.org...

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

   1  MGRLGYWTLLVLPALLVWRDPAQNAAAEKGPPALNIAVLLGHSHDVTERE    50
  51  LRNLWGPEQATGLPLDVNVVALLMNRTDPKSLITHVCDLMSGARIHGLVF   100
 101  GDDTDQEAVAQMLDFISSQTFIPILGIHGGASMIMADKDPTSTFFQFGAS   150
 151  IQQQATVMLKIMQDYDWHVFSLVTTIFPGYRDFISFIKTTVDNSFVGWDM   200
 201  QNVITLDTSFEDAKTQVQLKKIHSSVILLYCSKDEAVLILSEARSLGLTG   250
 251  YDFFWIVPSLVSGNTELIPKEFPSGLISVSYDDWDYSLEARVRDGLGILT   300
 301  TAASSMLEKFSYIPEAKASCYGQAEKPETPLHTLHQFMVNVTWDGKDLSF   350
 351  TEEGYQVHPRLVVIVLNKDREWEKVGKWENQTLSLRHAVWPRYKSFSDCE   400
 401  PDDNHLSIVTLEEAPFVIVEDIDPLTETCVRNTVPCRKFVKINNSTNEGM   450
 451  NVKKCCKGFCIDILKKLSRTVKFTYDLYLVTNGKHGKKVNNVWNGMIGEV   500
 501  VYQRAVMAVGSLTINEERSEVVDFSVPFVETGISVMVSRSNGTVSPSAFL   550
 551  EPFSASVWVMMFVMLLIVSAIAVFVFEYFSPVGYNRNLAKGKAPHGPSFT   600
 601  IGKAIWLLWGLVFNNSVPVQNPKGTTSKIMVSVWAFFAVIFLASYTANLA   650
 651  AFMIQEEFVDQVTGLSDKKFQRPHDYSPPFRFGTVPNGSTERNIRNNYPY   700
 701  MHQYMTRFNQRGVEDALVSLKTGKLDAFIYDAAVLNYKAGRDEGCKLVTI   750
 751  GSGYIFASTGYGIALQKGSPWKRQIDLALLQFVGDGEMEELETLWLTGIC   800
 801  HNEKNEVMSSQLDIDNMAGVFYMLAAAMALSLITFIWEHLFYWKLRFCFT   850
 851  GVCSDRPGLLFSISRGIYSCIHGVHIEEKKKSPDFNLTGSQSNMLKLLRS   900
 901  AKNISNMSNMNSSRMDSPKRATDFIQRGSLIVDMVSDKGNLIYSDNRSFQ   950
 951  GKDSIFGDNMNELQTFVANRHKDNLSNYVFQGQHPLTLNESNPNTVEVAV  1000
1001  STESKGNSRPRQLWKKSMESLRQDSLNQNPVSQRDEKTAENRTHSLKSPR  1050
1051  YLPEEVAHSDISETSSRATCHREPDNNKNHKTKDNFKRSMASKYPKDCSD  1100
1101  VDRTYMKTKASSPRDKIYTIDGEKEPSFHLDPPQFVENITLPENVGFPDT  1150
1151  YQDHNENFRKGDSTLPMNRNPLHNEDGLPNNDQYKLYAKHFTLKDKGSPH  1200
1201  SEGSDRYRQNSTHCRSCLSNLPTYSGHFTMRSPFKCDACLRMGNLYDIDE  1250
1251  DQMLQETGNPATREEVYQQDWSQNNALQFQKNKLRINRQHSYDNILDKPR  1300
1301  EIDLSRPSRSISLKDRERLLEGNLYGSLFSVPSSKLLGNKSSLFPQGLED  1350
1351  SKRSKSLLPDHASDNPFLHTYGDDQRLVIGRCPSDPYKHSLPSQAVNDSY  1400
1401  LRSSLRSTASYCSRDSRGHSDVYISEHVMPYAANKNTMYSTPRVLNSCSN  1450
1451  RRVYKKMPSIESDV                                      1464

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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