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

NucPred

Fetching Q6P5D3 from www.uniprot.org...

The NucPred score for your sequence is 0.79 (see score help below)

   1  MSSSVRRKGKPGKGDGKGSSRGGRGGKGHMNKSHGGGGGGGGSCGGGGGG    50
  51  SRKASNRIWDDGDDFCVFTEPKRPSRPCDSNKSKGETRPKWKPKAKVPLQ   100
 101  TLHMTSENQEKVKALLRDLQEQGADAGSERGTSGEEEDSEPQCGEEQGWP   150
 151  AGQEPIFLPDCSPWEYIGPEEVEPPVPECAVSPLAVQKLSRYGFHTEHCQ   200
 201  LALRICDGDLGAALEHLLRQCFSETFGERMALSEAAVYVSLNECVEQRQE   250
 251  ETLALKSICGEKFIERIQNRVWTIGLELDYLTNKFCKSKQKESSKNVRDT   300
 301  SPETCKFYLKGNCKFGSKCKFKHEVPPHQMIGRAERNVNDPHLDADDDTT   350
 351  FMYELQIRFSKDHKYPYQAPLVAFYSTNENLPLACRLHISEFLYGKALEF   400
 401  AKTSEPVVYSLITLLEEESEIVKLLTHTQHKYSVPPVNVPPVPSETRISK   450
 451  PAYRKPVVPSNTFLSNQMLEGERLSELEEDADEDEGPASIIVENESYVNL   500
 501  KKRSYKRYDRPAKSLFAENSKICRQFQMKQASRQFHAILQERQLLPAWEE   550
 551  RETILKLLSKHQVVVISGMTGCGKTTQIPQFILDNSLNGPPERVANIICT   600
 601  QPRRISAISVAERVAKERAERVGLTVGYQIRLESVKSSATRLLYCTTGVL   650
 651  LRRLEGDATLQGVTHIIVDEVHERTEESDFLLLVLKDIVMQRATLQVILM   700
 701  SATLDAGLFSKYFSYCPVITIPGRAFPVDQFFLEDALAVTRYVLQDGSPY   750
 751  MRSMKQIAKEKLKARHNRTAQEEVEEDLRLSLHLQDEEESVKDTIPDQQL   800
 801  DFKQLLIRYKGVSKSVIKTMSVMDFEKVNLELIEALLEWIVDGKHAYPPG   850
 851  AVLVFLPGLAEIKMLYEQLQSNSLFNNRRSHRCVIHPLHSSLSSEEQQAV   900
 901  FVKPPMGVTKIIISTNIAETSITIDDVVYVIDSGKMKEKRYDAGKGMESL   950
 951  EDTFVSQANALQRKGRAGRVASGVCFHLFTSHHYNHQLLKQQLPEIQRVP  1000
1001  LEQLCLRIKILEMFSTHNLQSVFSRLIEPPHIDSLRASKVRLRDLGALTP  1050
1051  DEKLTPLGYHLASLPVDVRIGKLMLLGSIFRCLDPALTIAASLAFKSPFV  1100
1101  SPWDKKEEANQKKLEFAFANSDYLALLCAYKGWQLSTKESARASYNYCRQ  1150
1151  NFLSGRTLQEMASLKRQFTELLSDIGFVKEGLRAKEIEKRAQGGDGVLDA  1200
1201  TGEEANTNAENPKLISAVLCAALYPNVVQVKTPEGKFQKTSSGVVRLQPK  1250
1251  SAELKFVTKNDGYVHIHPSSVNYQVRHFDSPYLLYHEKIKTSRVFIRDCS  1300
1301  MVSVYPLVLFGGGQVNVQLQRGAFVVSLDDGWIRFVAASHQVAELVKELR  1350
1351  CELDQLLQDKIKNPSMDLCSCPRGSRIISMIVKLITTQ              1388

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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