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

NucPred

Fetching P54623 from www.uniprot.org...

The NucPred score for your sequence is 0.88 (see score help below)

   1  MNSNRTSSSHNSRNLKILNASFDVPRPPGGGNSPLPSQGRSVRELEEQMS    50
  51  ALRKENFNLKLRIYFLEEGQPGARADSSTESLSKQLIDAKIEIATLRKTV   100
 101  DVKMELLKDAARAISHHEELQRKADIDSQAIIDELQEQIHAYQMAESGGQ   150
 151  PVENIAKTRKMLRLESEVQRLEEELVNIEARNVAARNELEFMLAERLESL   200
 201  TACEGKIQELAIKNSELVERLEKETASAESSNEAIDSLKVELEACRKENQ   250
 251  DLVTSIRTLKHDMKRQVRSMKEAANTMDVQRQSILLLEATIKRKEKSCGS   300
 301  MQKNVLNYEALIAKLNAELETMRQQNVYFRELSENLQQKEVRQLDRGVAI   350
 351  VQPMRMTADAGRFVWQSGTIVAQEPLPLERQSAAATSNVSVSAVRLSSGP   400
 401  PPDQTYPVNGHDRAKYGLLQLFAAKLDWISAVPLALGHLALKIILLAMRL   450
 451  HSCLQNVHIPLRANRDLGAQLADKICELQEAQEKLKERERIHEQACRTIQ   500
 501  KLMQKLSSQEKEIKKLNQENEQSANKENDCAKTVISPSSSGRSMSDNEAS   550
 551  SQEMSTNLRVRYELKINEQEEKIKQLQTEVKKKTANLQNLVNKELWEKNR   600
 601  EVERLTKLLANQQKTLPQISEESAGEADLQQSFTEAEYMRALERNKLLQR   650
 651  KVDVLFQRLADDQQNSAVIGQLRLELQQARTEVETADKWRLECVDVCSVL   700
 701  TNRLEELAGFLNSLLKHKDVLGVLAADRRNAMRKAVDRSLDLSKSLNMTL   750
 751  NITATSLADQSLAQLCNLSEILYTEGDASHKTFNSHEELHAATSMAPTVE   800
 801  NLKAENKALKKELEKRRSSEGQRKERRSLPLPSQQFDNQSESEAWSEPDR   850
 851  KVSLARIGLDETSNSLAAPEQAISESESEGRTCATRQDRNRNSERIAQLE   900
 901  EQIAQKDERMLNVQCQMVELDNRYKQEQLRCLDITQQLEQLRAINEALTA   950
 951  DLHAIGSHEEERMVELQRQLELKNQQIDQLKLAHSTLTADSQITEMELQA  1000
1001  LQQQMQEIEQLHADSVETLQSQLQKLKLDAVQQLEEHERLHREALERDWV  1050
1051  ALTTYQEQAQQLLELQRSLDYHQENEKELKQTLVENELATRALKKQLDES  1100
1101  TLQASKAVMERTKAYNDKLQLEKRSEELRLQLEALKEEHQKLLQKRSNSS  1150
1151  DVSQSGYTSEEVAVPMGPPSGQATTCKQAAAAVLGQRVNTSSPDLGIESD  1200
1201  AGRISSVEVSNAQRAMLKTVEMKTEGSASPKAKSEESTSPDSKSNVATGA  1250
1251  ATVHDCAKVDLENAELRRKLIRTKRAFEDTYEKLRMANKAKAQVEKDIKN  1300
1301  QILKTHNVLRNVRSNMENEL                                1320

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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