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

NucPred

Fetching Q5AW75 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MISATSFVTAIGSRPPRYRTPSPPRRAVEPISPCSTADYRTYRASREISA    50
  51  SATSDHVRSTPTDKRPSPADVPASHRSGHGRSSSTIDTLATIALATSPTF   100
 101  TPLTHRPPSDKSNTTLSMFPPETEPVERPAKRPRSERDESSYTQHRSNAF   150
 151  SIARPPAISDSMKTDAELLLNFARPTNLYPPIPSSKRANTDDSYHNHTFH   200
 201  TQAQIKERNASTYWVTNHENVIFNHSAMHNIPPSRMRSQSDGSAAISRPV   250
 251  IEGLRPNTSSSTLPPLAFQEEADSGDRHWDMERKPVLEESQVDFCKPDET   300
 301  VPILSQSQPLKKELDADSNGSSQASCATCNLVRIPVDNEDQDVTWISCDG   350
 351  CKRWFHIVCAGFKNDRETRTVDKFICKTCRPIHGQTTFVRKSSRVRTSID   400
 401  YAGLNQGLVKSATDSLEHHYIEPIKQNKIRFLPENFPRMRPELVTAEYFE   450
 451  KGNGMTEPIVIPAEFNTHATIPPTNPEFDALVQDAPSQEMFDELLDHLPN   500
 501  VDHETVIDCGQNQLDMVIPQGLTVRTVSELYGPEERVEVIDVKSQHGEDK   550
 551  RWTMQKWADYYESTGDKVVRNVISLEVSQSKLGRLIRRPKIVRDLDLQDA   600
 601  VWPEELKAVGNFPKVQFYCLMSVADCYTDFHIDFGGSSVYYHILKGKKTF   650
 651  FFIPPKDKHLKKYEEWCNSPAQDYTFLGDQTKECYRVDLSEGDTMLIPSG   700
 701  WIHAVWTPENSLVIGGNFLTRLNYGMQIKIAKIEKETKVPMKFRYPFFQK   750
 751  IQWYAVLKYLEEDPVPQSVLAAFSQDENYRFHRKYPIYYEFGERANTEPK   800
 801  GSPYHNSRFYSQAELEGLPDLAKYLLRTALIAGSYLVEGVTADTRNAVKR   850
 851  SIPAMPGEPIDVIRTFGVWIAWKRGNEKAAHWTRPGVVESNAKLSLAEKR   900
 901  PAGRPSRRSERNADNQRTYAERQAVQRLSERPAVDIQKDSAPGDESVAPL   950
 951  ANNSPPAATSGIPVPVMNEDTSQKHKTASRGSGLGPKRVACDACRKRRIR  1000
1001  CHHKEENNGASGSQMTVSTSSLGHHTPTAQDAASALNSLAAIASGAGFQN  1050
1051  GLHSIKGMDRMDASANFATSISATPHGVTLKVGDGSPDGLNSAKKGRSKA  1100
1101  CDDCRKSKRRCIHDEYGRIDPIKAQERSKPRATSLAKRPRVHEEAAPSSA  1150
1151  NKRLKQESTSPVAQPVHSSHMDTETPTRAQDSVENGVLDQYPRKSNTQHA  1200
1201  DGLPAEKALLPDQSSYASPPAFQADAVATKELPATVSKPAAVLVSPPTSL  1250
1251  ADEMDIHDQVDAGGEHVSVIYTPSSGSRQSSRQPRQVERYMPEVHFAKTA  1300
1301  KSTTTTPQTTRRSSFGSSGRKTTPGLSSGSKKSGSRPSSSHGKKSLSPSV  1350
1351  EKKAERHAISSAPFGQHGRGSKSEHGTSDVDPDAESLRLIREIQEQEFGL  1400
1401  RRRAGRA                                             1407

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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