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

NucPred

Fetching Q8HVY3 from www.uniprot.org...

The NucPred score for your sequence is 0.89 (see score help below)

   1  MAERANLVFHNKVIGGTAIKRLISRLIDHFGMAYTSHILDQVKTLGFRQA    50
  51  TDTSISLGIDDLLTIPSKGWLVQDAEQQSLILEQHHHYGNVHAVEKLRQS   100
 101  IEIWYATSEYFRQEMNPNFRMTDPFNPVHIMSFSGARGNASQVHQLVGMR   150
 151  GLMSDPQGQMIDLPIQSNLREGLSLTEYIISCYGARKGVVDTAVRTSDAG   200
 201  YLTRRLVEVVQHIVVRRTDCGTIQGISVNTQNGMMPERIWIQTLIGRVLA   250
 251  DDIYRGSRCIAVRNQDIGIGLINRFKTLQTQPISIRTPFTCRNTSWICRL   300
 301  CYGQSPTHGHLVELGEAVGIIAGQSIGEPGTQLTLRTFHTGGVFTGGTAE   350
 351  QVRAPYNGKIQFNEDLVHPTRTRHGHPAFLCYIDLYVTIESGDIIHNVTI   400
 401  PPKSFLLVQNNQYVKSEQVIAEIRAGTYTFNLKEKVRKHVYSDLEGEMHW   450
 451  STDVYHASEFRYSNVHILPKTSHLWILSGKSYRSGSVSFSIRKDQDQMNI   500
 501  HYLSTGERDFCNLLASKKKVRHKLFRFNPSDKKERRISDYSIFNQIISID   550
 551  HCHFTHPTIFHDTTDLLAKRRRNRLIIPFQFQSIQERDKELMLASSISIE   600
 601  IPINGIFRRNSILAYFDDPQYRTQSSGITKYRTIGINSIFKKEDFLIEYQ   650
 651  GVKEFKTKYQIKVDQFFFIPEEVHILPESSSIMVRNNSIVEVDTLITLNI   700
 701  RSRVRGLVRLEKKKKKIELKIFSGDIYFPGEMDKISRHSAVLIPPRTVKK   750
 751  NSKEKKMKNWIYVQWITITKKKYFVLVRPVILYEIADRINLVKLFPQDMF   800
 801  QERDNLELKVINYILSGNGKSIRGISDTSIQLVRTCLVLNWDQDKKFSSI   850
 851  ENAHASFVEISIKGLVRYFLRIDLVKSHISYIRKRNNPPGSRFILDNESD   900
 901  RTTINPFFSIDSREKIQQSLSKNHGTIRMLLNRNEKCRSLIILSSSNCFQ   950
 951  IRSFNHGKYYNGIKEGINQIQRDAMIPIKNSLGPLGIAPQVAHFDFYRLI  1000
1001  THNQISIIKNGQLDKLKETFQVFQYYFLDENERIYKPDLCSNIILNPFYL  1050
1051  NWHFLHHNYCEKTFTIMSLGQFICENVCIVQTKNAPHLKSGQILTVQMDS  1100
1101  VGIRSANPYLATPGATVHGHYGEILSEGDILVTFIYEKSRSGDITQGLPK  1150
1151  VEQVLEVRSIDSISMNLEKRVDTWNGRITKILGIPWGFLIGAELTIAQSR  1200
1201  ISLVNKIQKVYRSQGVHIHNRHIEIIVRQITSKVLVSEDGMSNVFLPGEL  1250
1251  IGLLRAERAGRSLEEAICYRVLLLGITKTSLNTQSFISEASFQETARVLS  1300
1301  KAALRGRIDWLKGLKENVVLGGMIPVGTGFKRIMNRSKQRQYNKMTSETK  1350
1351  KKNLFEGEMRDILFHHREFFFFVSKNLCDTSQQSSI                1386

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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