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

NucPred

Fetching P06213 from www.uniprot.org...

The NucPred score for your sequence is 0.66 (see score help below)

   1  MATGGRRGAAAAPLLVAVAALLLGAAGHLYPGEVCPGMDIRNNLTRLHEL    50
  51  ENCSVIEGHLQILLMFKTRPEDFRDLSFPKLIMITDYLLLFRVYGLESLK   100
 101  DLFPNLTVIRGSRLFFNYALVIFEMVHLKELGLYNLMNITRGSVRIEKNN   150
 151  ELCYLATIDWSRILDSVEDNYIVLNKDDNEECGDICPGTAKGKTNCPATV   200
 201  INGQFVERCWTHSHCQKVCPTICKSHGCTAEGLCCHSECLGNCSQPDDPT   250
 251  KCVACRNFYLDGRCVETCPPPYYHFQDWRCVNFSFCQDLHHKCKNSRRQG   300
 301  CHQYVIHNNKCIPECPSGYTMNSSNLLCTPCLGPCPKVCHLLEGEKTIDS   350
 351  VTSAQELRGCTVINGSLIINIRGGNNLAAELEANLGLIEEISGYLKIRRS   400
 401  YALVSLSFFRKLRLIRGETLEIGNYSFYALDNQNLRQLWDWSKHNLTITQ   450
 451  GKLFFHYNPKLCLSEIHKMEEVSGTKGRQERNDIALKTNGDQASCENELL   500
 501  KFSYIRTSFDKILLRWEPYWPPDFRDLLGFMLFYKEAPYQNVTEFDGQDA   550
 551  CGSNSWTVVDIDPPLRSNDPKSQNHPGWLMRGLKPWTQYAIFVKTLVTFS   600
 601  DERRTYGAKSDIIYVQTDATNPSVPLDPISVSNSSSQIILKWKPPSDPNG   650
 651  NITHYLVFWERQAEDSELFELDYCLKGLKLPSRTWSPPFESEDSQKHNQS   700
 701  EYEDSAGECCSCPKTDSQILKELEESSFRKTFEDYLHNVVFVPRKTSSGT   750
 751  GAEDPRPSRKRRSLGDVGNVTVAVPTVAAFPNTSSTSVPTSPEEHRPFEK   800
 801  VVNKESLVISGLRHFTGYRIELQACNQDTPEERCSVAAYVSARTMPEAKA   850
 851  DDIVGPVTHEIFENNVVHLMWQEPKEPNGLIVLYEVSYRRYGDEELHLCV   900
 901  SRKHFALERGCRLRGLSPGNYSVRIRATSLAGNGSWTEPTYFYVTDYLDV   950
 951  PSNIAKIIIGPLIFVFLFSVVIGSIYLFLRKRQPDGPLGPLYASSNPEYL  1000
1001  SASDVFPCSVYVPDEWEVSREKITLLRELGQGSFGMVYEGNARDIIKGEA  1050
1051  ETRVAVKTVNESASLRERIEFLNEASVMKGFTCHHVVRLLGVVSKGQPTL  1100
1101  VVMELMAHGDLKSYLRSLRPEAENNPGRPPPTLQEMIQMAAEIADGMAYL  1150
1151  NAKKFVHRDLAARNCMVAHDFTVKIGDFGMTRDIYETDYYRKGGKGLLPV  1200
1201  RWMAPESLKDGVFTTSSDMWSFGVVLWEITSLAEQPYQGLSNEQVLKFVM  1250
1251  DGGYLDQPDNCPERVTDLMRMCWQFNPKMRPTFLEIVNLLKDDLHPSFPE  1300
1301  VSFFHSEENKAPESEELEMEFEDMENVPLDRSSHCQREEAGGRDGGSSLG  1350
1351  FKRSYEEHIPYTHMNGGKKNGRILTLPRSNPS                    1382

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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