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

NucPred

Fetching Q07563 from www.uniprot.org...

The NucPred score for your sequence is 0.61 (see score help below)

   1  MDVTKKSKRDGTEVTERIVTETVTTRLTSLPPKGSTSNGYAKTGSLGGGS    50
  51  RLEKQSLTHGSSGYINSSGSIRGNASTSSYRRTHSPASTLPNSPGSTFER   100
 101  KAHMTRHGTYEGSSSGNSSPEYPRKELASSSTRGRSQTRESEIRVRLQSA   150
 151  SPSTRWTELDEVKRLLKGSRSASASPTRNTSNTLPIPKKGTVETKTVTAS   200
 201  SHSVSGTYDSAILDTNFPPHMWSSTLPAGSSLGTYQNNITAQSTSLLNTN   250
 251  AYSTGSVFGVPNNMASCSPTLHPGLSSCSSVFGMQNNLAPSSSVLSHGTT   300
 301  TASTAYGAKKNVPQPPTVTSTGVSTSATCTTSVQSDDLLHKDCKFLILEK   350
 351  DNTPAKKEMELLIMTKDSGKVFTASPATISSTSFSEDTLKKEKQAAYAAD   400
 401  TCLKADVNGDLNTVSTKSKMTSAENHGYDRGGGGGRGKGGGAGGGGGGGG   450
 451  ASGGGGAWGAAPAWCPCGSCCSWWKWLLGLLLTWLLLLGLLFGLIALAEE   500
 501  VRKLKARVEELEKTKVLYHDVQMDKSNRDRLQAEAPSLGPGLGKAELDGY   550
 551  SQEAIWLFVRNKLMTEQENGNLRGSPGPKGDMGSQGPKGDRGLPGTPGIP   600
 601  GPLGHPGPEGPKGQKGSIGDPGMEGPIGQRGLAGPMGPRGEPGPPGSGEK   650
 651  GDRGIAGEQGPQGLPGVPGPPGLRGHSGSPGPQGPPGAVGPQGLRGDVGL   700
 701  PGVKGDKGLMGPPGPKGDQGEKGPRGLTGEPGIRGLPGAVGEPGAKGAMG   750
 751  PAGADGQQGSRGEQGLTGMPGTRGPPGPAGDPGKPGLTGPQGPQGLPGSP   800
 801  GRPGTKGEPGAPGRVMTSEGSSTITVPGPPGPPGAMGPPGPPGTPGPAGP   850
 851  AGLPGQQGPRGEPGLAGDSFLSSGSSISEVLSAQGVDLRGPPGPPGPRGP   900
 901  PGPSIPGPPGPRGPPGEGVPGPPGPPGSFLTDSETFFTGPPGPPGPPGPK   950
 951  GDQGDPGVPGTPGISGGLSHGASSSTLYMQGPPGPPGPPGPPGSLSSSGQ  1000
1001  DIQHYIAEYMQSDNIRTYLSGVQGPPGPPGPPGPVITITGETFDYSQLAS  1050
1051  QVVSYLRSSGYGAGLSSASSSEDILAMLRRNDVWQYLRQNLVGPPGPPGP  1100
1101  PGVSGDGSLLSLDYGELSRHILNYMSSSGISFGHPGPPGPPGLPGTSYEE  1150
1151  LLTMLRGSDYRNIIGPPGPPGPPGMPGNAWSSISVEDLSSYLHTAGLSSI  1200
1201  PGPPGPPGPPGPRGPPGVSAALSTYAAENSDNFRSELISYLTSPDVRSFI  1250
1251  VGPPGPPGPQGPPGDGHLRENYNWSSNSSARRGTSYSSSTGTGGTNGGSL  1300
1301  GEGGAYGAGDGGPYGTDIGPGGGYGAAAGGGIYGTNGDSFRDGFTGDLDY  1350
1351  NKLAVRVSESMQRQGLLQGMAYTVQGPPGPQGPPGISRVFSAYSNVTQDL  1400
1401  MDFFQTYGTIPGPPGQKGDVGTPGPKGDRGPAGPRGPPGPPGPRGNKGEK  1450
1451  GDKGDQVYTGRRKRSIAIKP                                1470

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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