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

NucPred

Fetching Q5ZIX8 from www.uniprot.org...

The NucPred score for your sequence is 0.76 (see score help below)

   1  MVLRLEGSWSLLVGKRFLSLSGDDDGPWDTERVAEWPWQAGRIRAVSHTD    50
  51  ISKPDLKICVEFDDESWEKRRWIEVYSPKMKVFLVEQKLVLAERRSHGGS   100
 101  ISPVQWPAMTYKSLVDKAGLGPMVSIRYLGEEKCVFLSKDLLTPIQDVES   150
 151  SRLPLKDDQTVNEEIQALVKKHLDETRLVQGGKNIIGSKIRIYSLDPSTQ   200
 201  WFTAVVVNGNPATRTLEVNCQEIPALKTLDPELIHVEIIYDNNGKCDKSK   250
 251  RIGGVKRKPSENSGSVDAKHTKSSPEVSQSQGHVHSVPTVFGEALLGCTP   300
 301  ANKDQRHQGLPLPANSPPNLGAETPQGTCRRSVPEVHPSCLNAGTKPLKE   350
 351  NLTLFPKVTYITKEQTQNINDQNGKYTSLISSRSSSLSDSTNGKETGLKN   400
 401  ISEPLLKPTTNFPKECISAKPLQHLNSSIAIPRVNSSVELQRTLDCRPST   450
 451  SDAHLLPFTEAGVRSHSGSNSQKGNKVDEHVEMEFFTRRNSNEAFYERNE   500
 501  NESFWTGSTKIQDNVIVRKSILADASKVKKLQQSGEAFVQDGSCNNIAPH   550
 551  LHKCRECRLDSYRKNKDQKDSTVFCRFFHFRRLQFNKHGILREEGFLTPN   600
 601  KYDPEAISLWLPLSKNVVGLDLDTAKYILANIGDHFCQLVISEKEVMSTI   650
 651  EPHRQVAWKRAVRGVREMCDVCDTTIFNLRWVCSKCGFGVCVDCYRMRKK   700
 701  GIHEDDDSDTFSWFKCVKGQEHEPENLMPTQIIPGRALYDVGDIVHSVRT   750
 751  KWGIKANCPCANKQFKALSKPTLKEDSKQNLVPGERTSLQQSNLVLSPQL   800
 801  PTHEPPVKPAAGSKQTASVTTSPSLSWLSNITSGNVNKENKEKLLVPISK   850
 851  NENKALQTLPSLAKPAAALQTFNSAILTPVSNNNTGFLRNLLNSSGGKTD   900
 901  NGLKSTPKILDDIFASLVQNRTVTDMPKKPQGLTIKPTIMGFDTPHYWLC   950
 951  DNRLLCLQDPNNESNWNVFRECWKQGQPVMVSGVHHKLNADLWRPESFRK  1000
1001  EFGQQEVDLVNCRTNEIITGATVGDFWDGFEDISSRLRTEEGEPMVLKLK  1050
1051  DWPPGEDFRDMMPSRFDDLMKNIPLPEYTRRGGKLNLASRLPNYFVRPDL  1100
1101  GPKMYNAYGLITPEDRKYGTTNLHLDVSDAANVMVYVGIPKGQADQEEEV  1150
1151  LKTIQDGDSDELTIKRFTESREKPGALWHIYAAKDTEKIREFLKKVAEEQ  1200
1201  GQENPVDHDPIHDQSWYLDRSLRKRLHQEYGVQGWAIVQFLGDVVFIPAG  1250
1251  APHQVHNLYSCIKVAEDFVSPEHVKHCFWLTQEFRYLSHTHTNHEDKLQV  1300
1301  KNVIYHAVKDAVGILRANESSLSRS                           1325

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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