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

NucPred

Fetching Q6EW58 from www.uniprot.org...

The NucPred score for your sequence is 0.75 (see score help below)

   1  MEVLMAERADLVFHNKVIDGTAMKRLISRLIDHFGIAYTSHILDQVKTLG    50
  51  FQQATATSISLGIDDLLTTPSKRWLVQDAEQQSLILEKHHHYGNVHAVEK   100
 101  LRQSIEIWYATSEYLRQEMNLNFKMTDPSNPVHIMSYSGARGNASQVHQL   150
 151  VGMRGLMSDPQGQMIDLPIQSNLREGLSLTEYTISCYGARKGVVDTAVRT   200
 201  SDAGYLTRRLVEVVQHIVVRRTDCGSTRGISVSFRKGMTERIFIQTLIGR   250
 251  VLANDVYLGLRCIATRNQDIGIGLVNRFMTSRAQPIYIRTPFTCRSASWI   300
 301  CRLCYGRSPTHGDLVELGEAVGIIAGQSIGEPGTQLTLRTFHTGGVFTGG   350
 351  TAEHVRAPSNGKIKFNEDLVHPTRTRHGHPAFLCYVDLYVTIESQDIIHS   400
 401  VNIPPKSFLLVQNDQYVESEQVIAEIRAGTSTFHFKERVRKHIYSDSEGE   450
 451  MHWSTGVYHAPEYTHGNVHFLPKTSHLWILSGGPCKSSLVPFSLHKDQDQ   500
 501  MNVQSLSVQERSISDFSVNNNRVKHKLFGSDPLARKGRRISDYAAGSERV   550
 551  ISNGDGDFIYPAILRENSYLLAKRRRNRFIIPFQYDPEWEKELTPHSSTS   600
 601  ITVEIPANGILRRNSILAYFDDPRYRRSSSGITKYGIIEVDSIVKKEGLV   650
 651  EYRRPKESRPKYQMKVDRFFVIPEEVHILPGSSSIMVRNNSIIGVDTRIT   700
 701  FNTRSQIGGLVRIEKKKKIELKIFSGGIHFPGETDKISRHIGILIPPGAR   750
 751  KKMDKGSKGKNWEGNNWVYVQRITPIKKKYFVSVRPVVTYEIADGINLVT   800
 801  LFPGDMLQEKDNLRLQVVNYILYGDGKPIRGISHTSIQLVRTCLVLNWDQ   850
 851  DKKGSIEKVQASSAEVRANDLIRYFIRIDLVKSPILYTGKRNDRSGSVIP   900
 901  DTGSYCANTNLFSSKVKIKSLSQHQGTVRTFLNRNKEGQSLIVFSSSNCS   950
 951  RINVSKYHNVTKESIKEKEDTPIPILNLLGPLGTVPKIHNFSPSYHSITH  1000
1001  NEILLNKYLILDNKNPKQTFQLLKYYLVDENGRISNANPCSDIIFNLFGS  1050
1051  CFLPHDYCEGTSTTRIISLGQFICENVCLSKHGTRIKSGQVIMVYLDSFI  1100
1101  IRSAKPYLATRGATVHGDYGEIFYEGDTLVTFIYEKSRSGDITHGLPKVE  1150
1151  QVLEVRSIDSISMNLEKRVEGWNEHITGILGIPWGFLIGAELTIAQSRVS  1200
1201  LVNKIQKVYRSQGVQIHNKHIEIIVRQITSKVLVSEDGMSNVFSPGELIG  1250
1251  LLRAERAGRALEEAICYRAVLLGITRASLNTQSFISEASFQETARVLAKA  1300
1301  ALRGRIDWLKGLKENVVLGGMIPVGTGFKRFVHRSREYNNIPLEIQKKNF  1350
1351  FGGEMRDILFHHRELFCSCIPKPKSFHNTSEQPFYAMGSNPIVHKSGFII  1400
1401  S                                                   1401

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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