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

NucPred

Fetching P32657 from www.uniprot.org...

The NucPred score for your sequence is 0.99 (see score help below)

   1  MAAKDISTEVLQNPELYGLRRSHRAAAHQQNYFNDSDDEDDEDNIKQSRR    50
  51  KRMTTIEDDEDEFEDEEGEEDSGEDEDEEDFEEDDDYYGSPIKQNRSKPK   100
 101  SRTKSKSKSKPKSQSEKQSTVKIPTRFSNRQNKTVNYNIDYSDDDLLESE   150
 151  DDYGSEEALSEENVHEASANPQPEDFHGIDIVINHRLKTSLEEGKVLEKT   200
 201  VPDLNNCKENYEFLIKWTDESHLHNTWETYESIGQVRGLKRLDNYCKQFI   250
 251  IEDQQVRLDPYVTAEDIEIMDMERERRLDEFEEFHVPERIIDSQRASLED   300
 301  GTSQLQYLVKWRRLNYDEATWENATDIVKLAPEQVKHFQNRENSKILPQY   350
 351  SSNYTSQRPRFEKLSVQPPFIKGGELRDFQLTGINWMAFLWSKGDNGILA   400
 401  DEMGLGKTVQTVAFISWLIFARRQNGPHIIVVPLSTMPAWLDTFEKWAPD   450
 451  LNCICYMGNQKSRDTIREYEFYTNPRAKGKKTMKFNVLLTTYEYILKDRA   500
 501  ELGSIKWQFMAVDEAHRLKNAESSLYESLNSFKVANRMLITGTPLQNNIK   550
 551  ELAALVNFLMPGRFTIDQEIDFENQDEEQEEYIHDLHRRIQPFILRRLKK   600
 601  DVEKSLPSKTERILRVELSDVQTEYYKNILTKNYSALTAGAKGGHFSLLN   650
 651  IMNELKKASNHPYLFDNAEERVLQKFGDGKMTRENVLRGLIMSSGKMVLL   700
 701  DQLLTRLKKDGHRVLIFSQMVRMLDILGDYLSIKGINFQRLDGTVPSAQR   750
 751  RISIDHFNSPDSNDFVFLLSTRAGGLGINLMTADTVVIFDSDWNPQADLQ   800
 801  AMARAHRIGQKNHVMVYRLVSKDTVEEEVLERARKKMILEYAIISLGVTD   850
 851  GNKYTKKNEPNAGELSAILKFGAGNMFTATDNQKKLEDLNLDDVLNHAED   900
 901  HVTTPDLGESHLGGEEFLKQFEVTDYKADIDWDDIIPEEELKKLQDEEQK   950
 951  RKDEEYVKEQLEMMNRRDNALKKIKNSVNGDGTAANSDSDDDSTSRSSRR  1000
1001  RARANDMDSIGESEVRALYKAILKFGNLKEILDELIADGTLPVKSFEKYG  1050
1051  ETYDEMMEAAKDCVHEEEKNRKEILEKLEKHATAYRAKLKSGEIKAENQP  1100
1101  KDNPLTRLSLKKREKKAVLFNFKGVKSLNAESLLSRVEDLKYLKNLINSN  1150
1151  YKDDPLKFSLGNNTPKPVQNWSSNWTKEEDEKLLIGVFKYGYGSWTQIRD  1200
1201  DPFLGITDKIFLNEVHNPVAKKSASSSDTTPTPSKKGKGITGSSKKVPGA  1250
1251  IHLGRRVDYLLSFLRGGLNTKSPSADIGSKKLPTGPSKKRQRKPANHSKS  1300
1301  MTPEITSSEPANGPPSKRMKALPKGPAALINNTRLSPNSPTPPLKSKVSR  1350
1351  DNGTRQSSNPSSGSAHEKEYDSMDEEDCRHTMSAIRTSLKRLRRGGKSLD  1400
1401  RKEWAKILKTELTTIGNHIESQKGSSRKASPEKYRKHLWSYSANFWPADV  1450
1451  KSTKLMAMYDKITESQKK                                  1468

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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