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

NucPred

Fetching Q52KW0 from www.uniprot.org...

The NucPred score for your sequence is 0.94 (see score help below)

   1  MVTPRLQTMAESSKFKKKVHFGETRSDRTKKLFRHYTVGSYDSFDASSDC    50
  51  IIEEKTVVLQKKDNEGFGFVLRGAKADTPIEEFNPTPAFPALQYLESVDE   100
 101  DGVAWQAGLRTGDFLTEVNNENVVKVGHRQVVNMIRHGGNHLVLKVVTVT   150
 151  RNLDPDDTARKKAPPPPKRAPTTALSLRSKSMTSELEELAVDIASVRRRK   200
 201  DVQVSDVECLKRRIVIRVALNKSEESGPISKPLRPLDNTPVNSRVATVKQ   250
 251  RPTSRCFPAASDTNSMYDRQGIAVIPPTTPGSHQGPFLGIPRGTMRRQKS   300
 301  IDSRIPLSGITEEERQFLAPPMLKFTRSLSMPDASEDIPPPPATLPPSPP   350
 351  PPSPSSFNSPKSPAPRGYGTIKPAFTQNSGTKSPSPAVRSDNVGTIARDK   400
 401  SMYFRHEANRFSLDSEELYNSNMSTQQNFINKRSKMPENPYSEVGRLGNK   450
 451  GVYVPAKPVRRKGMLVKQSNVEDSPEKTCSIPIPTIIIKEPSTSSSGKSS   500
 501  QGSSMETDLQISEQVGQLRPDESLNVSGPFAAAIAGAVRDREKRLEARRN   550
 551  SPAFLSTDLGDECVGPKPSPRLQHSKSIDDGMFCSEEKAKHFMAPSSLII   600
 601  NRGSSNAFTNNDSSHQGDVSNARMSKIKGPENNAAPAKSTNASGNYMHPV   650
 651  TGKLLDPNSPLALALAARDRALKEQNQPSPSPTDPEKADLNKPLFIDTKL   700
 701  RSGMETINANRPNMRGMLKRQETESKHEPDSSKEEKRQGEKKNMLINIMD   750
 751  TSQQKTAGLLMVHTVDTTKADNVLTESEEAEKDPPPENSNSPVSEPREEL   800
 801  ENSIPKASECGTPAAPHIKAIVSVCSVEEPVILPFRIPPPPFASVDVDED   850
 851  FVFTEPLPPPLEFANSFDIPEDASQIPPASLADLLIQRKNRAFPPPSFNP   900
 901  NIASNSIESKRLAALSNCLPTSFMQHPESFDNVTDSGIEEVDSRSGSDHH   950
 951  LETTSTISTVSSISTLSSEGGENLDTCTVYADGQAFLVDKPPVPPKPKVK  1000
1001  PIINKSNALYKDAVLEENLDNFAVPLPAPPPLPLSIQPSMTKAGQQRTSK  1050
1051  LWGDNTEVKSLVMPSPKANVISELNSILQQMNREKATKTGEGLDSPTGMK  1100
1101  TASLSTRGTDALSTVSGNRNAAVTFTIRPGANQPISLQNRTPEFDSRVTG  1150
1151  MRRAPSPVVVSPAEIIRDIKPGPLSAPPASMSDVFILPSQPPSGDMFGMS  1200
1201  MGRSRSPSPSILQQPISNKPFSAKPIHMWTKQDVAEWLESLHLGEHREMF  1250
1251  MDNEIDGTHLPNLQKEDLIDLGVTRVGHRMNIERALKQLLDR          1292

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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