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

NucPred

Fetching Q13009 from www.uniprot.org...

The NucPred score for your sequence is 0.98 (see score help below)

   1  MGNAESQHVEHEFYGEKHASLGRKHTSRSLRLSHKTRRTRHASSGKVIHR    50
  51  NSEVSTRSSSTPSIPQSLAENGLEPFSQDGTLEDFGSPIWVDRVDMGLRP   100
 101  VSYTDSSVTPSVDSSIVLTAASVQSMPDTEESRLYGDDATYLAEGGRRQH   150
 151  SYTSNGPTFMETASFKKKRSKSADIWREDSLEFSLSDLSQEHLTSNEEIL   200
 201  GSAEEKDCEEARGMETRASPRQLSTCQRANSLGDLYAQKNSGVTANGGPG   250
 251  SKFAGYCRNLVSDIPNLANHKMPPAAAEETPPYSNYNTLPCRKSHCLSEG   300
 301  ATNPQISHSNSMQGRRAKTTQDVNAGEGSEFADSGIEGATTDTDLLSRRS   350
 351  NATNSSYSPTTGRAFVGSDSGSSSTGDAARQGVYENFRRELEMSTTNSES   400
 401  LEEAGSAHSDEQSSGTLSSPGQSDILLTAAQGTVRKAGALAVKNFLVHKK   450
 451  NKKVESATRRKWKHYWVSLKGCTLFFYESDGRSGIDHNSIPKHAVWVENS   500
 501  IVQAVPEHPKKDFVFCLSNSLGDAFLFQTTSQTELENWITAIHSACATAV   550
 551  ARHHHKEDTLRLLKSEIKKLEQKIDMDEKMKKMGEMQLSSVTDSKKKKTI   600
 601  LDQIFVWEQNLEQFQMDLFRFRCYLASLQGGELPNPKRLLAFASRPTKVA   650
 651  MGRLGIFSVSSFHALVAARTGETGVRRRTQAMSRSASKRRSRFSSLWGLD   700
 701  TTSKKKQGRPSINQVFGEGTEAVKKSLEGIFDDIVPDGKREKEVVLPNVH   750
 751  QHNPDCDIWVHEYFTPSWFCLPNNQPALTVVRPGDTARDTLELICKTHQL   800
 801  DHSAHYLRLKFLIENKMQLYVPQPEEDIYELLYKEIEICPKVTQSIHIEK   850
 851  SDTAADTYGFSLSSVEEDGIRRLYVNSVKETGLASKKGLKAGDEILEINN   900
 901  RAADALNSSMLKDFLSQPSLGLLVRTYPELEEGVELLESPPHRVDGPADL   950
 951  GESPLAFLTSNPGHSLCSEQGSSAETAPEETEGPDLESSDETDHSSKSTE  1000
1001  QVAAFCRSLHEMNPSDQSPSPQDSTGPQLATMRQLSDADKLRKVICELLE  1050
1051  TERTYVKDLNCLMERYLKPLQKETFLTQDELDVLFGNLTEMVEFQVEFLK  1100
1101  TLEDGVRLVPDLEKLEKVDQFKKVLFSLGGSFLYYADRFKLYSAFCASHT  1150
1151  KVPKVLVKAKTDTAFKAFLDAQNPKQQHSSTLESYLIKPIQRILKYPLLL  1200
1201  RELFALTDAESEEHYHLDVAIKTMNKVASHINEMQKIHEEFGAVFDQLIA  1250
1251  EQTGEKKEVADLSMGDLLLHTTVIWLNPPASLGKWKKEPELAAFVFKTAV  1300
1301  VLVYKDGSKQKKKLVGSHRLSIYEDWDPFRFRHMIPTEALQVRALASADA  1350
1351  EANAVCEIVHVKSESEGRPERVFHLCCSSPESRKDFLKAVHSILRDKHRR  1400
1401  QLLKTESLPSSQQYVPFGGKRLCALKGARPAMSRAVSAPSKSLGRRRRRL  1450
1451  ARNRFTIDSDAVSASSPEKESQQPPGGGDTDRWVEEQFDLAQYEEQDDIK  1500
1501  ETDILSDDDEFCESVKGASVDRDLQERLQATSISQRERGRKTLDSHASRM  1550
1551  AQLKKQAALSGINGGLESASEEVIWVRREDFAPSRKLNTEI           1591

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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