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

NucPred

Fetching P32660 from www.uniprot.org...

The NucPred score for your sequence is 0.66 (see score help below)

   1  MSGTFHGDGHAPMSPFEDTFQFEDNSSNEDTHIAPTHFDDGATSNKYSRP    50
  51  QVSFNDETPKNKREDAEEFTFNDDTEYDNHSFQPTPKLNNGSGTFDDVEL   100
 101  DNDSGEPHTNYDGMKRFRMGTKRNKKGNPIMGRSKTLKWARKNIPNPFED   150
 151  FTKDDIDPGAINRAQELRTVYYNMPLPKDMIDEEGNPIMQYPRNKIRTTK   200
 201  YTPLTFLPKNILFQFHNFANVYFLVLIILGAFQIFGVTNPGLSAVPLVVI   250
 251  VIITAIKDAIEDSRRTVLDLEVNNTKTHILEGVENENVSTDNISLWRRFK   300
 301  KANSRLLFKFIQYCKEHLTEEGKKKRMQRKRHELRVQKTVGTSGPRSSLD   350
 351  SIDSYRVSADYGRPSLDYDNLEQGAGEANIVDRSLPPRTDCKFAKNYWKG   400
 401  VKVGDIVRIHNNDEIPADIILLSTSDTDGACYVETKNLDGETNLKVRQSL   450
 451  KCTNTIRTSKDIARTKFWIESEGPHSNLYTYQGNMKWRNLADGEIRNEPI   500
 501  TINNVLLRGCTLRNTKWAMGVVMFTGGDTKIMLNSGITPTKKSRISRELN   550
 551  FSVVINFVLLFILCFVSGIANGVYYDKKGRSRFSYEFGTIAGSAATNGFV   600
 601  SFWVAVILYQSLVPISLYISVEIIKTAQAAFIYGDVLLYNAKLDYPCTPK   650
 651  SWNISDDLGQVEYIFSDKTGTLTQNVMEFKKCTINGVSYGRAYTEALAGL   700
 701  RKRQGIDVETEGRREKAEIAKDRDTMIDELRALSGNSQFYPEEVTFVSKE   750
 751  FVRDLKGASGEVQQRCCEHFMLALALCHSVLVEANPDNPKKLDLKAQSPD   800
 801  EAALVATARDVGFSFVGKTKKGLIIEMQGIQKEFEILNILEFNSSRKRMS   850
 851  CIVKIPGLNPGDEPRALLICKGADSIIYSRLSRQSGSNSEAILEKTALHL   900
 901  EQYATEGLRTLCIAQRELSWSEYEKWNEKYDIAAASLANREDELEVVADS   950
 951  IERELILLGGTAIEDRLQDGVPDCIELLAEAGIKLWVLTGDKVETAINIG  1000
1001  FSCNLLNNEMELLVIKTTGDDVKEFGSEPSEIVDALLSKYLKEYFNLTGS  1050
1051  EEEIFEAKKDHEFPKGNYAIVIDGDALKLALYGEDIRRKFLLLCKNCRAV  1100
1101  LCCRVSPSQKAAVVKLVKDSLDVMTLAIGDGSNDVAMIQSADVGIGIAGE  1150
1151  EGRQAVMCSDYAIGQFRYLARLVLVHGRWSYKRLAEMIPEFFYKNMIFAL  1200
1201  ALFWYGIYNDFDGSYLYEYTYMMFYNLAFTSLPVIFLGILDQDVNDTISL  1250
1251  VVPQLYRVGILRKEWNQRKFLWYMLDGLYQSIICFFFPYLVYHKNMIVTS  1300
1301  NGLGLDHRYFVGVYVTTIAVISCNTYVLLHQYRWDWFSGLFIALSCLVVF  1350
1351  AWTGIWSSAIASREFFKAAARIYGAPSFWAVFFVAVLFCLLPRFTYDSFQ  1400
1401  KFFYPTDVEIVREMWQHGHFDHYPPGYDPTDPNRPKVTKAGQHGEKIIEG  1450
1451  IALSDNLGGSNYSRDSVVTEEIPMTFMHGEDGSPSGYQKQETWMTSPKET  1500
1501  QDLLQSPQFQQAQTFGRGPSTNVRSSLDRTREQMIATNQLDNRYSVERAR  1550
1551  TSLDLPGVTNAASLIGTQQNN                               1571

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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