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

NucPred

Fetching Q28181 from www.uniprot.org...

The NucPred score for your sequence is 0.64 (see score help below)

   1  MLGWVQRVLPQPPGTPQKTKQEEEGTEPEPELEPKPETAPEETELEEVSL    50
  51  PPEEPCVGKEVAAVTLGPQGTQETALTPPTSLQAQVSVAPEAHSSPRGWV   100
 101  LTWLRKGVEKVVPQPAHSSRPSQNIAAGLESPDQQAGAQILGQCGTGGSD   150
 151  EPSEPSRAEDPGPGPWLLRWFEQNLEKMLPQPPKISEGWRDEPTDAALGP   200
 201  EPPGPALEIKPMLQAQESPSLPAPGPPEPEEEPIPEPQPTIQASSLPPPQ   250
 251  DSARLMAWILHRLEMALPQPVIRGKGGEQESDAPVTCDVQTISILPGEQE   300
 301  ESHLILEEVDPHWEEDEHQEGSTSTSPRTSEAAPADEEKGKVVEQTPREL   350
 351  PRIQEEKEDEEEEKEDGEEEEEEGREKEEEEGEEKEEEEGREKEEEEGEK   400
 401  KEEEGREKEEEEGGEKEDEEGREKEEEEGRGKEEEEGGEKEEEEGRGKEE   450
 451  VEGREEEEDEEEEQDHSVLLDSYLVPQSEEDRSEESETQDQSEVGGAQAQ   500
 501  GEVGGAQALSEESETQDQSEVGGAQDQSEVGGAQAQGEVGGAQEQDGVGG   550
 551  AQDQSTSHQELQEEALADSSGVPATEEHPELQVEDADADSRPLIAEENPP   600
 601  SPVQLPLSPAKSDTLAVPGSATGSLRKRLPSQDDEAEELKMLSPAASPVV   650
 651  AWSDPTSPQGTDDQDRATSTASQNSAIINDRLQELVKLFKERTEKVKEKL   700
 701  IDPDVTSDEESPKPSPAKKAPEPAPEVKPAEAGQVEEEHYCEMLCCKFKR   750
 751  RPWKKYQFPQSIDPLTNLMYILWLFFVVLAWNWNCWLIPVRWAFPYQTPD   800
 801  NIHLWLLMDYLCDLIYLLDITVFQMRLQFVRGGDIITDKKEMRNNYVKSQ   850
 851  RFKMDMLCLLPLDLLYLKFGVNPLLRLPRCLKYMAFFEFNNRLESILSKA   900
 901  YVYRVIRTTAYLLYSLHLNSCLYYWASAYEGLGSTHWVYDGVGNSYIRCY   950
 951  YWAVKTLITIGGLPDPRTLFEIVFQGLNYFTGVFAFSVMIGQMRDVVGAA  1000
1001  TAGQTYYRSCMDSTVKYMNFYKIPRSVQNRVKTWYEYTWHSQGMLDESEL  1050
1051  MVQLPDKMRLDLAIDVNYSIVSKVALFQGCDRQMIFDMLKRLRSVVYLPN  1100
1101  DYVCKKGEIGREMYIIQAGQVQVLGGPDGKSVLVTLKAGSVFGEISLLAV  1150
1151  GGGNRRTANVVAHGFTNLFILDKKDLNEILVHYPESQKLLRKKARRMLRN  1200
1201  NNKPKEKSVLILPPRAGTPKLFNAALAAAGKMGAKGGRGGRLALLRARLK  1250
1251  ELAALEAAARQQQLLEQAKSSEDAAVGEEGSASPEQPPRPEPPAPEAPAP  1300
1301  EPTAPEPLAPEAPAPEAPAPSSPPPASQERPEGDKDAARPEEHPVRIHVT  1350
1351  LGPDPSEQILLVEVPEKQEEKEKKEEETEEKEEGEEARKEKEEE        1394

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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