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

NucPred

Fetching Q04693 from www.uniprot.org...

The NucPred score for your sequence is 0.77 (see score help below)

   1  MWGGGKMAVVSLSPHTAKMRKLFGQASTTMAYDGLKREAERRTRSDHNIT    50
  51  MVAKDDELYLYHLTLKKQTNFVHSCIGHFVDLEAGSKREQSQLCVATETH   100
 101  LELYDTADGELKLIAKFQNLFATITSMKSLDLPHSGSRAKASNWPTFLAL   150
 151  TSDSGNLSIVQIIMHAGALRLKTLVNQPLTRTTLRRVSPISYMEIDPNGR   200
 201  CIILSSVEQNKLCFLVDYAQKLRISSPLEIIRPHMVTLDMAVVDVNFNNP   250
 251  CFVTLEIDNAATQLSVHLIFYVLELGLNHIVKKADYLVNPSANFVLSLPD   300
 301  LSRYNITTSLSDNNYDADYDTLFNPFVVIGFENHILVKDMNGFFSLKVEI   350
 351  PKRSITNSRHKNVTIISGIVQKLKNDFFVLLQSNHGDLFKLTVSPDTNDR   400
 401  NRPLVQLSYFDTIQNSHQLHIFKNGYLFALSEMNNNFLFQFEKLGVEKND   450
 451  FSNVLTSKDPNKSLVFEPSIKLQNLSILSQQLNLNPSIKSQIVSDSPLSI   500
 501  ATKHFTNNKIITLTNAVNYSNLISTSLPPNATKLWLIPDPATTGDNNTLL   550
 551  FITFPKKTMILQIDNESMEELTPDEATRSAFKLSQDTTIHTCLMGSHSII   600
 601  QVCTAELRHIVPTGKSRYSNKLTWVPPAGIRIVCATSSKTQLIISLSNYE   650
 651  LVYFKIDVSSDSLIELTTHPELDTMPSKVAIVQDTQHADLLAIADNEGMI   700
 701  KIMSLKDQKEDFLTVISLQLVSEKISDMIMVRDSSIGQLNLHVGLENGVY   750
 751  MKFHIGDVDGSFTDIKRRFLGLKPVSLSYLREISVSLNNEEEEEEEEDDD   800
 801  DEKEEEEINSSGAKWMSCVVCHSSSTWVSYTWKNVWTIRQLKDQNMLSCS   850
 851  KFVNADVAINGVCSISSSGRLNIGRVSNFPTLDNWFHVHESSVNKQENGG   900
 901  GDESNEEEEDEMEEEMEMLQISTFRPRTILSFPNNPKSILFIDNHSGKKQ   950
 951  CRISLQIDGECLKFGSSDHLYKILDDIDCVSAAIIDFTRQADHLIICAGD  1000
1001  KRLLTYKILVNKDKLSFDIELLHQTEIISPIHAMLKFKNFLLTAMGSTIV  1050
1051  LYGLGKKQLLRRSVTQTPVSITKIVSMHQWNYERLAVGDIHESVTLFIWD  1100
1101  PAGNVFIPYVDDSVKRHVTVLKFLDEATVIGADRYGNAWTLRSPPECEKI  1150
1151  MSNHDPSELSNGAIKYPLDVITLQQKLPNTYDCKFKFQLLNHFFVNDIIT  1200
1201  DFHILDSLSNSDRPGCIYMGLQGTVGCFIPLLSKGNVFMMGNIENIMAEA  1250
1251  DDTFYLDYESRKKNNNMRKEDDEEESGSVVLQGRHGIEDEIICEGSCSIL  1300
1301  GRDHQEYRSYYAPVRKVIDGDLCENFLRLSLNEQEFLAKNLKSVQVEDII  1350
1351  QTINEVRTNYM                                         1361

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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