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

NucPred

Fetching P11047 from www.uniprot.org...

The NucPred score for your sequence is 0.65 (see score help below)

   1  MRGSHRAAPALRPRGRLWPVLAVLAAAAAAGCAQAAMDECTDEGGRPQRC    50
  51  MPEFVNAAFNVTVVATNTCGTPPEEYCVQTGVTGVTKSCHLCDAGQPHLQ   100
 101  HGAAFLTDYNNQADTTWWQSQTMLAGVQYPSSINLTLHLGKAFDITYVRL   150
 151  KFHTSRPESFAIYKRTREDGPWIPYQYYSGSCENTYSKANRGFIRTGGDE   200
 201  QQALCTDEFSDISPLTGGNVAFSTLEGRPSAYNFDNSPVLQEWVTATDIR   250
 251  VTLNRLNTFGDEVFNDPKVLKSYYYAISDFAVGGRCKCNGHASECMKNEF   300
 301  DKLVCNCKHNTYGVDCEKCLPFFNDRPWRRATAESASECLPCDCNGRSQE   350
 351  CYFDPELYRSTGHGGHCTNCQDNTDGAHCERCRENFFRLGNNEACSSCHC   400
 401  SPVGSLSTQCDSYGRCSCKPGVMGDKCDRCQPGFHSLTEAGCRPCSCDPS   450
 451  GSIDECNIETGRCVCKDNVEGFNCERCKPGFFNLESSNPRGCTPCFCFGH   500
 501  SSVCTNAVGYSVYSISSTFQIDEDGWRAEQRDGSEASLEWSSERQDIAVI   550
 551  SDSYFPRYFIAPAKFLGKQVLSYGQNLSFSFRVDRRDTRLSAEDLVLEGA   600
 601  GLRVSVPLIAQGNSYPSETTVKYVFRLHEATDYPWRPALTPFEFQKLLNN   650
 651  LTSIKIRGTYSERSAGYLDDVTLASARPGPGVPATWVESCTCPVGYGGQF   700
 701  CEMCLSGYRRETPNLGPYSPCVLCACNGHSETCDPETGVCNCRDNTAGPH   750
 751  CEKCSDGYYGDSTAGTSSDCQPCPCPGGSSCAVVPKTKEVVCTNCPTGTT   800
 801  GKRCELCDDGYFGDPLGRNGPVRLCRLCQCSDNIDPNAVGNCNRLTGECL   850
 851  KCIYNTAGFYCDRCKDGFFGNPLAPNPADKCKACNCNLYGTMKQQSSCNP   900
 901  VTGQCECLPHVTGQDCGACDPGFYNLQSGQGCERCDCHALGSTNGQCDIR   950
 951  TGQCECQPGITGQHCERCEVNHFGFGPEGCKPCDCHPEGSLSLQCKDDGR  1000
1001  CECREGFVGNRCDQCEENYFYNRSWPGCQECPACYRLVKDKVADHRVKLQ  1050
1051  ELESLIANLGTGDEMVTDQAFEDRLKEAEREVMDLLREAQDVKDVDQNLM  1100
1101  DRLQRVNNTLSSQISRLQNIRNTIEETGNLAEQARAHVENTERLIEIASR  1150
1151  ELEKAKVAAANVSVTQPESTGDPNNMTLLAEEARKLAERHKQEADDIVRV  1200
1201  AKTANDTSTEAYNLLLRTLAGENQTAFEIEELNRKYEQAKNISQDLEKQA  1250
1251  ARVHEEAKRAGDKAVEIYASVAQLSPLDSETLENEANNIKMEAENLEQLI  1300
1301  DQKLKDYEDLREDMRGKELEVKNLLEKGKTEQQTADQLLARADAAKALAE  1350
1351  EAAKKGRDTLQEANDILNNLKDFDRRVNDNKTAAEEALRKIPAINQTITE  1400
1401  ANEKTREAQQALGSAAADATEAKNKAHEAERIASAVQKNATSTKAEAERT  1450
1451  FAEVTDLDNEVNNMLKQLQEAEKELKRKQDDADQDMMMAGMASQAAQEAE  1500
1501  INARKAKNSVTSLLSIINDLLEQLGQLDTVDLNKLNEIEGTLNKAKDEMK  1550
1551  VSDLDRKVSDLENEAKKQEAAIMDYNRDIEEIMKDIRNLEDIRKTLPSGC  1600
1601  FNTPSIEKP                                           1609

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.)

Go back to the NucPred Home Page.