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

NucPred

Fetching P40457 from www.uniprot.org...

The NucPred score for your sequence is 0.99 (see score help below)

   1  MEDKISEFLNVPFESLQGVTYPVLRKLYKKIAKFERSEEEVTKLNVLVDE    50
  51  IKSQYYSRISKLKQLLDESSEQKNTAKEELNGLKDQLNEERSRYRREIDA   100
 101  LKKQLHVSHEAMREVNDEKRVKEEYDIWQSRDQGNDSLNDDLNKENKLLR   150
 151  RKLMEMENILQRCKSNAISLQLKYDTSVQEKELMLQSKKLIEEKLSSFSK   200
 201  KTLTEEVTKSSHVENLEEKLYQMQSNYESVFTYNKFLLNQNKQLSQSVEE   250
 251  KVLEMKNLKDTASVEKAEFSKEMTLQKNMNDLLRSQLTSLEKDCSLRAIE   300
 301  KNDDNSCRNPEHTDVIDELIDTKLRLEKSKNECQRLQNIVMDCTKEEEAT   350
 351  MTTSAVSPTVGKLFSDIKVLKRQLIKERNQKFQLQNQLEDFILELEHKTP   400
 401  ELISFKERTKSLEHELKRSTELLETVSLTKRKQEREITSLRQKINGCEAN   450
 451  IHSLVKQRLDLARQVKLLLLNTSAIQETASPLSQDELISLRKILESSNIV   500
 501  NENDSQAIITERLVEFSNVNELQEKNVELLNCIRILADKLENYEGKQDKT   550
 551  LQKVENQTIKEAKDAIIELENINAKMETRINILLRERDSYKLLASTEENK   600
 601  ANTNSVTSMEAAREKKIRELEAELSSTKVENSAIIQNLRKELLIYKKSQC   650
 651  KKKTTLEDFENFKGLAKEKERMLEEAIDHLKAELEKQKSWVPSYIHVEKE   700
 701  RASTELSQSRIKIKSLEYEISKLKKETASFIPTKESLTRDFEQCCKEKKE   750
 751  LQMRLKESEISHNENKMDFSSKEGQYKAKIKELENNLERLRSDLQSKIQE   800
 801  IESIRSCKDSQLKWAQNTIDDTEMKMKSLLTELSNKETTIEKLSSEIENL   850
 851  DKELRKTKFQYKFLDQNSDASTLEPTLRKELEQIQVQLKDANSQIQAYEE   900
 901  IISSNENALIELKNELAKTKENYDAKIELEKKEKWAREEDLSRLRGELGE   950
 951  IRALQPKLKEGALHFVQQSEKLRNEVERIQKMIEKIEKMSTIVQLCKKKE  1000
1001  MSQYQSTMKENKDLSELVIRLEKDAADCQAELTKTKSSLYSAQDLLDKHE  1050
1051  RKWMEEKADYERELISNIEQTESLRVENSVLIEKVDDTAANNGDKDHLKL  1100
1101  VSLFSNLRHERNSLETKLTTCKRELAFVKQKNDSLEKTINDLQRTQTLSE  1150
1151  KEYQCSAVIIDEFKDITKEVTQVNILKENNAILQKSLKNVTEKNREIYKQ  1200
1201  LNDRQEEISRLQRDLIQTKEQVSINSNKILVYESEMEQCKQRYQDLSQQQ  1250
1251  KDAQKKDIEKLTNEISDLKGKLSSAENANADLENKFNRLKKQAHEKLDAS  1300
1301  KKQQAALTNELNELKAIKDKLEQDLHFENAKVIDLDTKLKAHELQSEDVS  1350
1351  RDHEKDTYRTLMEEIESLKKELQIFKTANSSSDAFEKLKVNMEKEKDRII  1400
1401  DERTKEFEKKLQETLNKSTSSEAEYSKDIETLKKEWLKEYEDETLRRIKE  1450
1451  AEENLKKRIRLPSEERIQKIISKRKEELEEEFRKKLKENAGSLTFLDNKG  1500
1501  SGEDAEEELWNSPSKGNSERPSAVAGFINQKNLKPQEQLKNVKNDVSFND  1550
1551  SQSMVTNKENNIVDSSAAGNKAIPTFSFGKPFFSSNTSSLQSFQNPFTAS  1600
1601  QSNINTNAPLRTLNIQPEVAVKAAINFSNVTDLTNNSTDGAKITEIGSTS  1650
1651  KRPIESGTSSDPDTKKVKESPANDQASNE                       1679

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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