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

NucPred

Fetching Q5VXU9 from www.uniprot.org...

The NucPred score for your sequence is 0.94 (see score help below)

   1  MTDTSVLDQWKASFFVEDFLEKKTITRMVTQINCEFEEVVPSSNPDSQIE    50
  51  VEEVSLYTHMDYNEVFTPVSCLEKCSALQNQNQDLFIDDKGILFVSSRKH   100
 101  LPTLPTLLSRLKLFLVKDPLLDFKGQIFTEANFSRECFSLQETLEAFVKE   150
 151  DFCMDKVNFCQEKLEDTICLNEPSSFLIEYEFLIPPSLKPEIDIPSLSEL   200
 201  KELLNPVPEIINYVDEKEKLFERDLTNKHGIEDIGDIKFSSTEILTIQSQ   250
 251  SEPEECSKPGELEMPLTPLFLTCQHSSVNSLRTELQTFPLSPVCKINLLT   300
 301  AEESANEYYMMWQLERCRSPLNPFLLTVPRIQEPHSQYSVTDLKKIFSVK   350
 351  EESLVINLEKAEWWKQAGLNLKMMETLEHLNTYLCHDNLSSNDTKIEIFL   400
 401  PTKVLQLESCLEHKSHSSPIALIDEKSTNAHLSLPQKSPSLAKEVPDLCF   450
 451  SDDYFSDKGAAKEEKPKNDQEPVNRIIQKKENNDHFELDCTGPSIKSPSS   500
 501  SIIKKASFEHGKKQENDLDLLSDFIMLRNKYKTCTSKTEVTNSDEKHDKE   550
 551  ACSLTLQEESPIVHINKTLEEINQERGTDSVIEIQASDSQCQAFCLLEAA   600
 601  ASPILKNLVSLCTLPTANWKFATVIFDQTRFLLKEQEKVVSDAVRQGTID   650
 651  EREMTFKHAALLHLLVTIRDVLLTCSLDTALGYLSKAKDIYNSILGPYLG   700
 701  DIWRQLEIVQFIRGKKPETNYKIQELQCQILSWMQSQQQIKVLIIIRMDS   750
 751  DGEKHFLIKILNKIEGLTLTVLHSNERKDFLESEGVLRGTSSCVVVHNQY   800
 801  IGADFPWSNFSFVVEYNYVEDSCWTKHCKELNIPYMAFKVILPDTVLERS   850
 851  TLLDRFGGFLLEIQIPYVFFASEGLLNTPDILQLLESNYNISLVERGCSE   900
 901  SLKLFGSSECYVVVTIDEHTAIILQDLEELNYEKASDNIIMRLMALSLQY   950
 951  RYCWIILYTKETLNSEYLLTEKTLHHLALIYAALVSFGLNSEELDVKLII  1000
1001  APGVEATALIIRQIADHSLMTSKRDPHEWLDKSWLKVSPSEEEMYLLDFP  1050
1051  CINPLVAQLMLNKGPSLHWILLATLCQLQELLPEVPEKVLKHFCSITSLF  1100
1101  KIGSSSITKSPQISSPQENRNQISTLSSQSSASDLDSVIQEHNEYYQYLG  1150
1151  LGETVQEDKTTILNDNSSIMELKEISSFLPPVTSYNQTSYWKDSSCKSNI  1200
1201  GQNTPFLINIESRRPAYNSFLNHSDSESDVFSLGLTQMNCETIKSPTDTQ  1250
1251  KRVSVVPRFINSQKRRTHEAKGFINKDVSDPIFSLEGTQSPLHWNFKKNI  1300
1301  WEQENHPFNLQYGAQQTACNKLYSQKGNLFTDQQKCLSDESEGLTCESSK  1350
1351  DETFWRELPSVPSLDLFRASDSNANQKEFNSLYFYQRAGKSLGQKRHHES  1400
1401  SFNSGDKESLTGFMCSQLPQFKKRRLAYEKVPGRVDGQTRLRFF        1444

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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