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

NucPred

Fetching Q8TDM6 from www.uniprot.org...

The NucPred score for your sequence is 1.00 (see score help below)

   1  MEPQRRELLAQCQQSLAQAMTEVEAVLGLLEAAGALSPGERRQLDEEAGG    50
51 AKAELLLKLLLAKERDHFQDLRAALEKTQPHLLPILYLNGVVGPPQPAEG 100
101 AGSTYSVLSTMPSDSESSSSLSSVGTTGKAPSPPPLLTDQQVNEKVENLS 150
151 IQLRLMTRERNELRKRLAFATHGTAFDKRPYHRLNPDYERLKIQCVRAMS 200
201 DLQSLQNQHTNALKRCEEVAKETDFYHTLHSRLLSDQTRLKDDVDMLRRE 250
251 NGQLLRERNLLQQSWEDMKRLHEEDQKEIGDLRAQQQQVLKHNGSSEILN 300
301 KLYDTAMDKLEVVKKDYDALRKRYSEKVAIHNADLSRLEQLGEENQRLLK 350
351 QTEMLTQQRDTAIQLQHQCALSLRRFEAIHHELNKATAQNKDLQWEMELL 400
401 QSELTELRTTQVKTAKESEKYREERDAVYSEYKLIMSERDQVISELDKLQ 450
451 TEVELAESKLKSSTSEKKAANEEMEALRQIKDTVTMDAGRANKEVEILRK 500
501 QCKALCQELKEALQEADVAKCRRDWAFQERDKIVAERDSIRTLCDNLRRE 550
551 RDRAVSELAEALRSLDDTRKQKNDVSRELKELKEQMESQLEKEARFRQLM 600
601 AHSSHDSAIDTDSMEWETEVVEFERETEDIDLKALGFDMAEGVNEPCFPG 650
651 DCGIFVTKVDKGSIADGRLRVNDWLLRINDVDLINKDKKQAIKALLNGEG 700
701 AINMVVRRRKSLGGKVVTPLHINLSGQKDSGISLENGVYAAAVLPGSPAA 750
751 KEGSLAVGDRIVAINGIALDNKSLNECESLLRSCQDSLTLSLLKVFPQSS 800
801 SWSGQNIFENIKDSDKMLSFRAHGPEVQAHNKRNLIQHNNSTQTDIFYTD 850
851 RLEDRKEPGPPGGSSSFLHKPFPGGPLQVCPQACPSASERSLSSFRSDAS 900
901 GDRGFGLVDVRGRRPLLPFETEVGPCGVGEASLDKADSEGSNSGGTWPKA 950
951 MLSSTAVPEKLSVYKKPKQRKSIFDPNTFKRPQTPPKIDYLLPGPGPAHS 1000
1001 PQPSKRAGPLTPPKPPRRSDSIKFQHRLETSSESEATLVGSSPSTSPPSA 1050
1051 LPPDVDPGEPMHASPPRKARVRIASSYYPEGDGDSSHLPAKKSCDEDLTS 1100
1101 QKVDELGQKRRRPKSAPSFRPKLAPVVIPAQFLEEQKCVPASGELSPELQ 1150
1151 EWAPYSPGHSSRHSNPPLYPSRPSVGTVPRSLTPSTTVSSILRNPIYTVR 1200
1201 SHRVGPCSSPPAARDAGPQGLHPSVQHQGRLSLDLSHRTCSDYSEMRATH 1250
1251 GSNSLPSSARLGSSSNLQFKAERIKIPSTPRYPRSVVGSERGSVSHSECS 1300
1301 TPPQSPLNIDTLSSCSQSQTSASTLPRIAVNPASLGERRKDRPYVEEPRH 1350
1351 VKVQKGSEPLGISIVSGEKGGIYVSKVTVGSIAHQAGLEYGDQLLEFNGI 1400
1401 NLRSATEQQARLIIGQQCDTITILAQYNPHVHQLSSHSRSSSHLDPAGTH 1450
1451 STLQGSGTTTPEHPSVIDPLMEQDEGPSTPPAKQSSSRIAGDANKKTLEP 1500
1501 RVVFIKKSQLELGVHLCGGNLHGVFVAEVEDDSPAKGPDGLVPGDLILEY 1550
1551 GSLDVRNKTVEEVYVEMLKPRDGVRLKVQYRPEEFTKAKGLPGDSFYIRA 1600
1601 LYDRLADVEQELSFKKDDILYVDDTLPQGTFGSWMAWQLDENAQKIQRGQ 1650
1651 IPSKYVMDQEFSRRLSMSEVKDDNSATKTLSAAARRSFFRRKHKHKRSGS 1700
1701 KDGKDLLALDAFSSDSIPLFEDSVSLAYQRVQKVDCTALRPVLILGPLLD 1750
1751 VVKEMLVNEAPGKFCRCPLEVMKASQQAIERGVKDCLFVDYKRRSGHFDV 1800
1801 TTVASIKEITEKNRHCLLDIAPHAIERLHHMHIYPIVIFIHYKSAKHIKE 1850
1851 QRDPIYLRDKVTQRHSKEQFEAAQKLEQEYSRYFTGVIQGGALSSICTQI 1900
1901 LAMVNQEQNKVLWIPACPL 1919

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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