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

NucPred

Fetching Q9UKP4 from www.uniprot.org...

The NucPred score for your sequence is 0.66 (see score help below)

   1  MPGGPSPRSPAPLLRPLLLLLCALAPGAPGPAPGRATEGRAALDIVHPVR    50
  51  VDAGGSFLSYELWPRALRKRDVSVRRDAPAFYELQYRGRELRFNLTANQH   100
 101  LLAPGFVSETRRRGGLGRAHIRAHTPACHLLGEVQDPELEGGLAAISACD   150
 151  GLKGVFQLSNEDYFIEPLDSAPARPGHAQPHVVYKRQAPERLAQRGDSSA   200
 201  PSTCGVQVYPELESRRERWEQRQQWRRPRLRRLHQRSVSKEKWVETLVVA   250
 251  DAKMVEYHGQPQVESYVLTIMNMVAGLFHDPSIGNPIHITIVRLVLLEDE   300
 301  EEDLKITHHADNTLKSFCKWQKSINMKGDAHPLHHDTAILLTRKDLCAAM   350
 351  NRPCETLGLSHVAGMCQPHRSCSINEDTGLPLAFTVAHELGHSFGIQHDG   400
 401  SGNDCEPVGKRPFIMSPQLLYDAAPLTWSRCSRQYITRFLDRGWGLCLDD   450
 451  PPAKDIIDFPSVPPGVLYDVSHQCRLQYGAYSAFCEDMDNVCHTLWCSVG   500
 501  TTCHSKLDAAVDGTRCGENKWCLSGECVPVGFRPEAVDGGWSGWSAWSIC   550
 551  SRSCGMGVQSAERQCTQPTPKYKGRYCVGERKRFRLCNLQACPAGRPSFR   600
 601  HVQCSHFDAMLYKGQLHTWVPVVNDVNPCELHCRPANEYFAEKLRDAVVD   650
 651  GTPCYQVRASRDLCINGICKNVGCDFEIDSGAMEDRCGVCHGNGSTCHTV   700
 701  SGTFEEAEGLGYVDVGLIPAGAREIRIQEVAEAANFLALRSEDPEKYFLN   750
 751  GGWTIQWNGDYQVAGTTFTYARRGNWENLTSPGPTKEPVWIQLLFQESNP   800
 801  GVHYEYTIHREAGGHDEVPPPVFSWHYGPWTKCTVTCGRGVQRQNVYCLE   850
 851  RQAGPVDEEHCDPLGRPDDQQRKCSEQPCPARWWAGEWQLCSSSCGPGGL   900
 901  SRRAVLCIRSVGLDEQSALEPPACEHLPRPPTETPCNRHVPCPATWAVGN   950
 951  WSQCSVTCGEGTQRRNVLCTNDTGVPCDEAQQPASEVTCSLPLCRWPLGT  1000
1001  LGPEGSGSGSSSHELFNEADFIPHHLAPRPSPASSPKPGTMGNAIEEEAP  1050
1051  ELDLPGPVFVDDFYYDYNFINFHEDLSYGPSEEPDLDLAGTGDRTPPPHS  1100
1101  HPAAPSTGSPVPATEPPAAKEEGVLGPWSPSPWPSQAGRSPPPPSEQTPG  1150
1151  NPLINFLPEEDTPIGAPDLGLPSLSWPRVSTDGLQTPATPESQNDFPVGK  1200
1201  DSQSQLPPPWRDRTNEVFKDDEEPKGRGAPHLPPRPSSTLPPLSPVGSTH  1250
1251  SSPSPDVAELWTGGTVAWEPALEGGLGPVDSELWPTVGVASLLPPPIAPL  1300
1301  PEMKVRDSSLEPGTPSFPTPGPGSWDLQTVAVWGTFLPTTLTGLGHMPEP  1350
1351  ALNPGPKGQPESLSPEVPLSSRLLSTPAWDSPANSHRVPETQPLAPSLAE  1400
1401  AGPPADPLVVRNAGWQAGNWSECSTTCGLGAVWRPVRCSSGRDEDCAPAG  1450
1451  RPQPARRCHLRPCATWHSGNWSKCSRSCGGGSSVRDVQCVDTRDLRPLRP  1500
1501  FHCQPGPAKPPAHRPCGAQPCLSWYTSSWRECSEACGGGEQQRLVTCPEP  1550
1551  GLCEEALRPNTTRPCNTHPCTQWVVGPWGQCSGPCGGGVQRRLVKCVNTQ  1600
1601  TGLPEEDSDQCGHEAWPESSRPCGTEDCEPVEPPRCERDRLSFGFCETLR  1650
1651  LLGRCQLPTIRTQCCRSCSPPSHGAPSRGHQRVARR                1686

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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