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

NucPred

Fetching Q8VD65 from www.uniprot.org...

The NucPred score for your sequence is 0.80 (see score help below)

   1  MGNQLAGIAPSQILSVESYFSDIHDFEYDKSLGSTRFFKVARAKHREGLV    50
  51  VVKVFAIQDPTLPLTSYKQELEELKIRLHSAQNCLPFQKAAEKASEKAAM   100
 101  LFRQYVRDNLYDRISTRPFLNNIEKRWIAFQILTAVDQAHKSGVRHGDIK   150
 151  TENVMVTSWNWVLLTDFASFKPTYLPEDNPADFNYFFDTSRRRTCYIAPE   200
 201  RFVDGGMFATELEYMRDPSTPLVDLNSNQRARGELKRAMDIFSAGCVIAE   250
 251  LFTEGVPLFDLSQLLAYRNGHFFPEQVLNKIEDRSIRDLVTQMINREPEK   300
 301  RLEAEDYLKQQRGNAFPEIFYTFLQPYMAQFAKETFLSADERILVIRKDL   350
 351  GNIIHNLCGHDLPEKAEGESRASGLVVLVSVITSCLQTLKSCDSKLAALE   400
 401  LILHLAPRLSVEILLDRITPYLLHFSNDSVPRVRAEALRTLTKVLALVQE   450
 451  VPRNDVNIYPEYILPGIAHLAQDDATIVRLAYAENIALLAETALRFLELV   500
 501  QLKTLNMENEPDNEEVDEATRPNGDYDTELQALHEMVQQKVVTLLSDPEN   550
 551  IVKQTLMESGITRLCVFFGRQKANDVLLSHMITFLNDKNDWHLRGAFFDS   600
 601  IVGVAAYVGWQSSSILKPLLQQGLSDAEEFVIVKALNALTCMCQLGLLQK   650
 651  PHVYEFASDIAPFLCHPNLWIRYGAVGFITVVAHQISTADVYCKLMPYLD   700
 701  PYITQPVIQIERKLVLLSVLKEPVSRSIFDYALRSKDIASLFRHLHMRQK   750
 751  KRNGSLLDCPPPEDPTIAQLLKKLLSQGMTEEEEDKLLALKDFMMKSNRA   800
 801  KANAVDQSHLHDSSQKGVIDLAALGITGRQVDLVKTKQEPDEKRARKHVK   850
 851  QDSNVNEEWKSMFGSLEPPNIPQALPKTSDHEVVQPGKPPRSESSAGICV   900
 901  PLSTSPQVSEAAHIPSKKPVIPVVSSTVLPSTYQIRITTCKTELQQLIQQ   950
 951  KREQCNAERIAKQMMENAEWESKPPPPGWRPKGLLVAHLHEHKSAVNRIR  1000
1001  VSDEHLLFATCSNDGTVKIWNSQKMEGKTTTTRSILTYSRIGGRVKTLTF  1050
1051  CQGSHYLAIASDNGAVQLLGIEASKLPKSPKIHPLQSRILDQKEDGCVVD  1100
1101  MHHFNSGAQSVLAYATVNGSLVGWDLRSSSNAWTLKHDLKSGLITSFAVD  1150
1151  IHQCWLCIGTSSGAMACWDMRFQLPISSHCHPSRARIRRLSMHPLYQSWV  1200
1201  IAAVQGNNEVSMWDMETGDRRLTLWASSAPPLSELQPSPHSVHGIYCSPA  1250
1251  DGNPILLTAGSDMKIRFWDLVSPERSYVVAGSTGSPSVSYYKKIIEGTEV  1300
1301  VQEIQNKQKVGPSDDTPRRGPESLPVGHHDIITDIATFQTTQGFIVTASR  1350
1351  DGIVKVWK                                            1358

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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