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

NucPred

Fetching Q9H582 from www.uniprot.org...

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

   1  MRSFLQQDVNKTKSRLNVLNGLANNMDDLKINTDITGAKEELLDDNNFIS    50
  51  DKESGVHKPKDCQTSFQKNNTLTLPEELSKDKSENALSGGQSSLFIHAGA   100
 101  PTVSSENFILPKGAAVNGPVSHSSLTKTSNMNKGSVSLTTGQPVDQPTTE   150
 151  SCSTLKVAADLQLSTPQKASQHQVLFLLSDVAHAKNPTHSNKKLPTSASV   200
 201  GCDIQNSVGSNIKSDGTLINQVEVGEDGEDLLVKDDCVNTVTGISSGTDG   250
 251  FRSENDTNWDPQKEFIQFLMTNEETVDKAPPHSKIGLEKKRKRKMDVSKI   300
 301  TRYTEDCFSDSNCVPNKSKMQEVDFLEQNEELQAVDSQKYALSKVKPEST   350
 351  DEDLESVDAFQHLIYNPDKCGEESSPVHTSTFLSNTLKKKCEESDSESPA   400
 401  TFSTEEPSFYPCTKCNVNFREKKHLHRHMMYHLDGNSHFRHLNVPRPYAC   450
 451  RECGRTFRDRNSLLKHMIIHQERRQKLMEEIRELKELQDEGRSARLQCPQ   500
 501  CVFGTNCPKTFVQHAKTHEKDKRYYCCEECNFMAVTENELECHRGIAHGA   550
 551  VVKCPMVTSDIAQRKTQKKTFMKDSVVGSSKKSATYICKMCPFTTSAKSV   600
 601  LKKHTEYLHSSSCVDSFGSPLGLDKRKNDILEEPVDSDSTKTLTKQQSTT   650
 651  FPKNSALKQDVKRTFGSTSQSSSFSKIHKRPHRIQKARKSIAQSGVNMCN   700
 701  QNSSPHKNVTIKSSVDQKPKYFHQAAKEKSNAKANSHYLYRHKYENYRMI   750
 751  KKSGESYPVHFKKEEASSLNSLHLFSSSSNSHNNFISDPHKPDAKRPESF   800
 801  KDHRRVAVKRVIKESKKESSVGGEDLDSYPDFLHKMTVVVLQKLNSAEKK   850
 851  DSYETEDESSWDNVELGDYTTQAIEDETYSDINQEHVNLFPLFKSKVEGQ   900
 901  EPGENATLSYDQNDGFYFEYYEDTGSNNFLHEIHDPQHLETADASLSKHS   950
 951  SVFHWTDLSLEKKSCPYCPATFETGVGLSNHVRGHLHRAGLSYEARHVVS  1000
1001  PEQIATSDKMQHFKRTGTGTPVKRVRKAIEKSETTSEHTCQLCGGWFDTK  1050
1051  IGLSNHVRGHLKRLGKTKWDAHKSPICVLNEMMQNEEKYEKILKALNSRR  1100
1101  IIPRPFVAQKLASSDDFISQNVIPLEAYRNGLKTEALSVSASEEEGLNFL  1150
1151  NEYDETKPELPSGKKNQSLTLIELLKNKRMGEERNSAISPQKIHNQTARK  1200
1201  RFVQKCVLPLNEDSPLMYQPQKMDLTMHSALDCKQKKSRSRSGSKKKMLT  1250
1251  LPHGADEVYILRCRFCGLVFRGPLSVQEDWIKHLQRHIVNANLPRTGAGM  1300
1301  VEVTSLLKKPASITETSFSLLMAEAAS                         1327

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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