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

NucPred

Fetching Q14689 from www.uniprot.org...

The NucPred score for your sequence is 0.37 (see score help below)

   1  MADRGCPLEAAPLPAEVRESLAELELELSEGDITQKGYEKKRAKLLARYI    50
  51  PLIQGIDPSLQAENRIPGPSQTTAAAPKQQKSRPTASRDERFRSDVHTEA   100
 101  VQAALAKYKERKMPMPSKRRSVLVHSSVETYTPPDTSSASEDEGSLRRPG   150
 151  RLTSTPLQSHSSVEPWLDRVIQGSSTSSSASSTSSHPGGRPTTAPSAAAT   200
 201  PGAAATTALAGLEAHTHIDLHSAPPDVTTGLVEHSYFERPQVASVRSVPR   250
 251  GCSGSMLETADGVPVNSRVSSKIQQLLNTLKRPKRPPLKEFFVDDFEELL   300
 301  EVQQPDPNQPKPEGSETSVLRGEPLTAGVPRPPSLLATLQRWGTTQPKSP   350
 351  CLTALDTTGKAVYTLTYGKLWSRSLKLAYTLLNKLTSKNEPLLKPGDRVA   400
 401  LVFPNSDPVMFMVAFYGCLLAELVPVPIEVPLTRKDAGSQQVGFLLGSCG   450
 451  VFLALTTDACQKGLPKAQTGEVAAFKGWPPLSWLVIDGKHLAKPPKDWHP   500
 501  LAQDTGTGTAYIEYKTSKEGSTVGVTVSHASLLAQCRALTQACGYSEAET   550
 551  LTNVLDFKRDAGLWHGVLTSVMNRMHVVSVPYALMKANPLSWIQKVCFYK   600
 601  ARAALVKSRDMHWSLLAQRGQRDVSLSSLRMLIVADGANPWSISSCDAFL   650
 651  NVFQSRGLRPEVICPCASSPEALTVAIRRPPDLGGPPPRKAVLSMNGLSY   700
 701  GVIRVDTEEKLSVLTVQDVGQVMPGANVCVVKLEGTPYLCKTDEVGEICV   750
 751  SSSATGTAYYGLLGITKNVFEAVPVTTGGAPIFDRPFTRTGLLGFIGPDN   800
 801  LVFIVGKLDGLMVTGVRRHNADDVVATALAVEPMKFVYRGRIAVFSVTVL   850
 851  HDDRIVLVAEQRPDASEEDSFQWMSRVLQAIDSIHQVGVYCLALVPANTL   900
 901  PKAPLGGIHISETKQRFLEGTLHPCNVLMCPHTCVTNLPKPRQKQPEVGP   950
 951  ASMIVGNLVAGKRIAQASGRELAHLEDSDQARKFLFLADVLQWRAHTTPD  1000
1001  HPLFLLLNAKGTVTSTATCVQLHKRAERVAAALMEKGRLSVGDHVALVYP  1050
1051  PGVDLIAAFYGCLYCGCVPVTVRPPHPQNLGTTLPTVKMIVEVSKSACVL  1100
1101  TTQAVTRLLRSKEAAAAVDIRTWPTILDTDDIPKKKIASVFRPPSPDVLA  1150
1151  YLDFSVSTTGILAGVKMSHAATSALCRSIKLQCELYPSRQIAICLDPYCG  1200
1201  LGFALWCLCSVYSGHQSVLVPPLELESNVSLWLSAVSQYKARVTFCSYSV  1250
1251  MEMCTKGLGAQTGVLRMKGVNLSCVRTCMVVAEERPRIALTQSFSKLFKD  1300
1301  LGLPARAVSTTFGCRVNVAICLQGTAGPDPTTVYVDMRALRHDRVRLVER  1350
1351  GSPHSLPLMESGKILPGVKVIIAHTETKGPLGDSHLGEIWVSSPHNATGY  1400
1401  YTVYGEEALHADHFSARLSFGDTQTIWARTGYLGFLRRTELTDASGGRHD  1450
1451  ALYVVGSLDETLELRGMRYHPIDIETSVIRAHRSIAECAVFTWTNLLVVV  1500
1501  VELDGLEQDALDLVALVTNVVLEEHYLVVGVVVIVDPGVIPINSRGEKQR  1550
1551  MHLRDGFLADQLDPIYVAYNM                               1571

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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