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

NucPred

Fetching Q9VKJ3 from www.uniprot.org...

The NucPred score for your sequence is 0.66 (see score help below)

   1  MPTSKLQANMSYREVIPRNLSPAEWIEVKINTGTQSTLQDLKTFETSGGY    50
  51  CYKNTKNVQTRNRFIYWRTYQDVLELSEVSLDISLQRNHLRLRFTDSAVL   100
 101  NVSLTEQGTSVTLLVVTVSSVHRYVFPLKVAGQEGGAASPEDLLSQSIFY   150
 151  DVNDKINDPSTYYVTDGFGTMPNAAVSYLTQDSQSAYFAVAYQSKLLLHV   200
 201  MKCSTGHTITHEIKEPKLMPWFLSNLKGALTGRSETLEAATSMAFSEIGG   250
 251  EIFILVLYRNNELRLWSVDNLQTVASINCSTELGQDSAAQGPQNSQLRKI   300
 301  SDQNFCLFLSHNSRAEFICVSIMPDADDASVINLVQNMVPAPQTDLVDFD   350
 351  ATSSHIWALWSNAEGDFHVSAAYFASNNAIKWVSAALEPPPDRYCLTMEQ   400
 401  GVDPRETYCSYIFHPGRFDRNVIAKALYMFRRVNLQFDVKQLSMSVLKEQ   450
 451  VCQAVEDEIQNELKDFVVTDEEYLEISTRLWDRFYSCCEQYHIKLSEPTG   500
 501  LAVLGGMDAVCLVRRQSFALLRPCEVLEHLLLIGEHNDEVATYVAPLFRN   550
 551  DPEMAKGFVELMNVVTLLDKLISEDIKIELDKQLYQRESPVEVISKLVAR   600
 601  ISMIDDNGPILPSNCVRQIQQKLQNIPNLEPALEMLLDVLCMIDPDEPPH   650
 651  DYSLSTRFLQSSGALMGSEYGLSILSETVKQMAMIRFSVCRNLLVLQYMA   700
 701  YGQNEMESENVLTNLNYLNSYYTLVWIAETPISSSTPAGFEASIQRLSRA   750
 751  QLFSGYNRPYSSHLKHNGNDQTTLLRLFLESKGLFSALTMLLKHDSLSLD   800
 801  SEQLNLRQSLLQLVGYINKMLWPGSPIYVFPEWLFGTCHHIIVQDYVRIL   850
 851  SNWCSVQKHARRFMLAVSLLDCGEAHKAVHLFHEAESGIVEDDFLFEHVL   900
 901  KNTPLYGKLQNSVSRGDTISPEDTKLAIVHYYLKVIQLFEQHSALDYIIQ   950
 951  LADMAIRVLQPDDPQLPMFQSIVFNNHLQLGHYVEAYTALVNNADISRRK  1000
1001  DCLRQLVITLFQNKCLPLLMQFSYIGLQDEFESIVESRARSMSIDQNEVY  1050
1051  NFLYAFHTNKGNMRKASTVMYEQAMRFQVDSDAPNALEKRCSSLLICLNC  1100
1101  LHLVDSRYRWIAKPVLGDEQVITIDQDNDDGEPKCDEDKRGQEVVVLELA  1150
1151  DIRRELVHAEALRELSFYRKDTAAYERATPEELSYLLASSGLYTAALKLS  1200
1201  RGHSFSVLPIFESLTSACVAATEDKSSDAWNWLQNNDMADLPHRSNAADM  1250
1251  AWTLLQKLVVDNEAKDSTLIRKSVVQRLLGLNAFLPQWLINSYKLSHSRE  1300
1301  LLHLLVKHNRLLEAADLGCEIIAGMLGAGSEYFEFKHAVNIANPQLCFPI  1350
1351  STIDLLLHGLKINGKDDLDYEMAYFKLEEEVQRYIETIKRTTDDKMSMAV  1400
1401  LQMRTDLQEER                                         1411

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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