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

NucPred

Fetching Q62190 from www.uniprot.org...

The NucPred score for your sequence is 0.41 (see score help below)

   1  MGLPLPLLQSSLLLMLLLRLSAASTNLNWQCPRIPYAASRDFSVKYVVPS    50
  51  FSAGGRVQATAAYEDSTNSAVFVATRNHLHVLGPDLQFIENLTTGPIGNP   100
 101  GCQTCASCGPGPHGPPKDTDTLVLVMEPGLPALVSCGSTLQGRCFLHELE   150
 151  PRGKALHLAAPACLFSANNNKPEACTDCVASPLGTRVTVVEQGHASYFYV   200
 201  ASSLDPELAASFSPRSVSIRRLKSDTSGFQPGFPSLSVLPKYLASYLIKY   250
 251  VYSFHSGDFVYFLTVQPISVTSPPSALHTRLVRLNAVEPEIGDYRELVLD   300
 301  CHFAPKRRRRGAPEGTQPYPVLQAAHSAPVDAKLAVELSISEGQEVLFGV   350
 351  FVTVKDGGSGMGPNSVVCAFPIYHLNILIEEGVEYCCHSSNSSSLLSRGL   400
 401  DFFQTPSFCPNPPGGEASGPSSRCHYFPLMVHASFTRVDLFNGLLGSVKV   450
 451  TALHVTRLGNVTVAHMGTVDGRVLQVEIARSLNYLLYVSNFSLGSSGQPV   500
 501  HRDVSRLGNDLLFASGDQVFKVPIQGPGCRHFLTCWRCLRAQRFMGCGWC   550
 551  GDRCDRQKECPGSWQQDHCPPEISEFYPHSGPLRGTTRLTLCGSNFYLRP   600
 601  DDVVPEGTHQITVGQSPCRLLPKDSSSPRPGSLKEFIQELECELEPLVTQ   650
 651  AVGTTNISLVITNMPAGKHFRVEGISVQEGFSFVEPVLTSIKPDFGPRAG   700
 701  GTYLTLEGQSLSVGTSRAVLVNGTQCRLEQVNEEQILCVTPPGAGTARVP   750
 751  LHLQIGGAEVPGSWTFHYKEDPIVLDISPKCGYSGSHIMIHGQHLTSAWH   800
 801  FTLSFHDGQSTVESRCAGQFVEQQQRRCRLPEYVVRNPQGWATGNLSVWG   850
 851  DGAAGFTLPGFRFLPPPSPLRAGLVELKPEEHSVKVEYVGLGAVADCVTV   900
 901  NMTVGGEVCQHELRGDVVICPLPPSLQLGKDGVPLQVCVDGGCHILSQVV   950
 951  RSSPGRASQRILLIALLVLILLVAVLAVALIFNSRRRKKQLGAHSLSPTT  1000
1001  LSDINDTASGAPNHEESSESRDGTSVPLLRTESIRLQDLDRMLLAEVKDV  1050
1051  LIPHEQVVIHTDQVIGKGHFGVVYHGEYTDGAQNQTHCAIKSLSRITEVQ  1100
1101  EVEAFLREGLLMRGLHHPNILALIGIMLPPEGLPRVLLPYMRHGDLLHFI  1150
1151  RSPQRNPTVKDLVSFGLQVACGMEYLAEQKFVHRDLAARNCMLDESFTVK  1200
1201  VADFGLARGVLDKEYYSVRQHRHARLPVKWMALESLQTYRFTTKSDVWSF  1250
1251  GVLLWELLTRGAPPYPHIDPFDLSHFLAQGRRLPQPEYCPDSLYHVMLRC  1300
1301  WEADPAARPTFRALVLEVKQVVASLLGDHYVQLTAAYVNVGPRAVDDGSV  1350
1351  PPEQVQPSPQHCRSTSKPRPLSEPPLPT                        1378

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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