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

NucPred

Fetching P04933 from www.uniprot.org...

The NucPred score for your sequence is 0.77 (see score help below)

   1  MKIIFFLCSFLFFIINTQCVTHESYQELVKKLEALEDAVLTGYSLFQKEK    50
  51  MVLNEGTSGTAVTTSTPGSKGSVASGGSGGSVASGGSVASGGSVASGGSV   100
 101  ASGGSGNSRRTNPSDNSSDSDAKSYADLKHRVRNYLLTIKELKYPQLFDL   150
 151  TNHMLTLCDNIHGFKYLIDGYEEINELLYKLNFYFDLLRAKLNDVCANDY   200
 201  CQIPFNLKIRANELDVLKKLVFGYRKPLDNIKDNVGKMEDYIKKNKKTIE   250
 251  NINELIEESKKTIDKNKNATKEEEKKKLYQAQYDLSIYNKQLEEAHNLIS   300
 301  VLEKRIDTLKKNENIKELLDKINEIKNPPPANSGNTPNTLLDKNKKIEEH   350
 351  EKEIKEIAKTIKFNIDSLFTDPLELEYYLREKNKNIDISAKVETKESTEP   400
 401  NEYPNGVTYPLSYNDINNALNELNSFGDLINPFDYTKEPSKNIYTDNERK   450
 451  KFINEIKEKIKIEKKKIESDKKSYEDRSKSLNDITKEYEKLLNEIYDSKF   500
 501  NNNIDLTNFEKMMGKRYSYKVEKLTHHNTFASYENSKHNLEKLTKALKYM   550
 551  EDYSLRNIVVEKELKYYKNLISKIENEIETLVENIKKDEEQLFEKKITKD   600
 601  ENKPDEKILEVSDIVKVQVQKVLLMNKIDELKKTQLILKNVELKHNIHVP   650
 651  NSYKQENKQEPYYLIVLKKEIDKLKVFMPKVESLINEEKKNIKTEGQSDN   700
 701  SEPSTEGEITGQATTKPGQQAGSALEGDSVQAQAQEQKQAQPPVPVPVPE   750
 751  AKAQVPTPPAPVNNKTENVSKLDYLEKLYEFLNTSYICHKYILVSHSTMN   800
 801  EKILKQYKITKEEESKLSSCDPLDLLFNIQNNIPVMYSMFDSLNNSLSQL   850
 851  FMEIYEKEMVCNLYKLKDNDKIKNLLEEAKKVSTSVKTLSSSSMQPLSLT   900
 901  PQDKPEVSANDDTSHSTNLNNSLKLFENILSLGKNKNIYQELIGQKSSEN   950
 951  FYEKILKDSDTFYNESFTNFVKSKADDINSLNDESKRKKLEEDINKLKKT  1000
1001  LQLSFDLYNKYKLKLERLFDKKKTVGKYKMQIKKLTLLKEQLESKLNSLN  1050
1051  NPKHVLQNFSVFFNKKKEAEIAETENTLENTKILLKHYKGLVKYYNGESS  1100
1101  PLKTLSEESIQTEDNYASLENFKVLSKLEGKLKDNLNLEKKKLSYLSSGL  1150
1151  HHLIAELKEVIKNKNYTGNSPSENNTDVNNALESYKKFLPEGTDVATVVS  1200
1201  ESGSDTLEQSQPKKPASTHVGAESNTITTSQNVDDEVDDVIIVPIFGESE  1250
1251  EDYDDLGQVVTGEAVTPSVIDNILSKIENEYEVLYLKPLAGVYRSLKKQL  1300
1301  ENNVMTFNVNVKDILNSRFNKRENFKNVLESDLIPYKDLTSSNYVVKDPY  1350
1351  KFLNKEKRDKFLSSYNYIKDSIDTDINFANDVLGYYKILSEKYKSDLDSI  1400
1401  KKYINDKQGENEKYLPFLNNIETLYKTVNDKIDLFVIHLEAKVLNYTYEK  1450
1451  SNVEVKIKELNYLKTIQDKLADFKKNNNFVGIADLSTDYNHNNLLTKFLS  1500
1501  TGMVFENLAKTVLSNLLDGNLQGMLNISQHQCVKKQCPQNSGCFRHLDER  1550
1551  EECKCLLNYKQEGDKCVENPNPTCNENNGGCDADAKCTEEDSGSNGKKIT  1600
1601  CECTKPDSYPLFDGIFCSSSNFLGISFLLILMLILYSFI             1639

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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