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

NucPred

Fetching Q2QLC5 from www.uniprot.org...

The NucPred score for your sequence is 0.86 (see score help below)

   1  MQRSPLEKASVVSKLFFSWTRPILKKGYRQRLELSDIYQIPSADSADNLS    50
51 EILEREWDRELASKKNPKLINALRRCFFWRFMFYGILLYLGEVTKAVQPL 100
101 LLGRIIASYDPDNKVERSIAIYLGIGLCLLFILRTLLLHPAIFGLHHIGM 150
151 QMRIAMFSLIYKKTLKLSSRVLDKISIGQLVSLLSNNLNKFDEGLALAHF 200
201 VWIAPLQVTLLMGLLWELLQASAFYGLAALIVVALLQAFLGRMMMKYRDQ 250
251 RAGKINERLVITSEIIENIQSVKAYCWEEAMEQMIENLRKTELKLTQKAA 300
301 YVRYVNSSGFFASGFFVVLFSVLPYLLNEGIILRKIFTTISFCIVLRMAV 350
351 TRQFPWAVQTWYDSIGAINKIQDFLQKQEFKTLEYNLTTTEVVMENVTAF 400
401 WDEGFGELFENAKQNSKNRNISNSDNSLFFSNFSLLGTPVLRDINFQIER 450
451 GQLLAIAGSTGAGKTSLLMMLLGELEPSEGKIKHSGRISFCSQFSWIMPG 500
501 TIKENIIFGVCYDEYRYRSVIKACQLEEDISKFAEKDNVVLGEGGLTLSG 550
551 GQRARICLARAVYKDADLYLLDSPFGHLDVLTEKQIFESCVCKLMANKTR 600
601 ILVTSKMEHLKKADKILILHEGSSYFYGTFSELQNLRPDFHSKLMGYDSF 650
651 DQFSAERRNSILTETLRRFSLEGDAAIPWNETKKQSFKQTGEFGEKRKNS 700
701 ILNPINSAKKFSVVQKTPLQMNGIEEDSEEPSERRLSLVPDSEQGEAILP 750
751 RSNVINTGPTFQKRRRQSVLNLMTHSSVNQCQIIHQKTAPSTRKMSLAPQ 800
801 GDLAEMDIYSRRLSQGSGLEISEEINEEDLKECFFDDMESIPTVTTWNTY 850
851 LRYVTAHKSLSFVLIWCLVLFLAEVAAFLVLLWHFKEKPPQDRGNSTGST 900
901 NSSNAFIVTNTSHFYLFYIYVGVADSLFALGFIRGLPLVHSLITVSKILH 950
951 HKMLHSVLHAPMSTLNMLKAGEILNRFSKDTAILDDLLPLTIFDFIQLAL 1000
1001 IVIGAIAVVSVLQPYIFLATVPVITAFITLRAYFLPTSQQLKQLESEGRS 1050
1051 PIFTHLVTSLRGLWTLRAFGRQPYFEALFHKALNLHTANWFLYLSTLRWF 1100
1101 QMRIEMIFVIFFIAVTFISILTTGEGEGRVGIILTLAMNIMSTLQWAMNS 1150
1151 SIDVDSLMRSVSRVFKFIDMPTEESKSTKLIKPSKDDKLTKVMIIENQHV 1200
1201 KKDDLWPLGGQMTIKNLIAKYTDNGNAILENISFSISPGQRVGLLGRTGS 1250
1251 GKSTLLSALLRLLNTEGEIQIDGVSWDSVTLQQWRKAFGVIPQKVFIFSG 1300
1301 TFRKNLDPYEQWNDEEIWKVADEVGLRSVIEQFPGKLDFVLLDGGFVLSH 1350
1351 GHKQLLCLARSVLSKAKILLLDEPSAHLDPITYQIIRRTLKQAFADCTVI 1400
1401 LSEHRIEAMLECQQFLVIEENKVRQYDSLQKLLSEKILFQQAMSPLDRLK 1450
1451 LLPHRNSSRHKSQSKISALKEETEEEVQETRL 1482

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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