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

NucPred

Fetching O54827 from www.uniprot.org...

The NucPred score for your sequence is 0.88 (see score help below)

   1  MERELPAAEESASSGWRRPRRRRWEGRTRTVRSNLLPPLGTEDSTIGAPK    50
  51  GERLLMRGCIQHLADNRLKTTKYTLLSFLPKNLFEQFHRLANVYFVFIAL   100
 101  LNFVPAVNAFQPGLALAPVLFILAVTAIKDLWEDYSRHRSDHEINHLGCL   150
 151  VFSREEKKYVNRYWKEIRVGDFVRLCCNEIIPADILLLSSSDPDGLCHIE   200
 201  TANLDGETNLKRRQVVRGFSELVSEFNPLTFTSVIECEKPNNDLSRFRGY   250
 251  IMHSNGEKAGLHKENLLLRGCTIRNTEAVAGIVIYAGHETKALLNNSGPR   300
 301  YKRSQLERQMNCDVLWCVLLLVCISLFSAVGHGLWVRRYQEKKALFDVPE   350
 351  SDGSSLSPATAAVYSFFTMIIVLQVLIPISLYVSIEIVKVCQVYFINQDI   400
 401  ELYDEETDSQLQCRALNITEDLGQIKYIFSDKTGTLTENKMVFRRCTVSG   450
 451  IEYSHDANAQRLARYQEADSEEEEVVSKVGTISHRGSTGSHQSIWMTHKT   500
 501  QSIKSHRRTGSRAEAKRASMLSKHTAFSSPMEKDITPDPKLLEKVSECDR   550
 551  FLAIARHQEHPLAHLSPELSDVFDFFIALTICNTVVVTSPDQPRQKVRVR   600
 601  FELKSPVKTIEDFLRRFTPSRLASGCSSIGNLSTSKSSHKSGSAFLPSLS   650
 651  QDSMLLGLEEKLGQTAPSIASNGYASQAGQEESWASECTTDQKCPGEQRE   700
 701  QQEGELRYEAESPDEAALVYAARAYNCALVDRLHDQVSVELPHLGRLTFE   750
 751  LLHTLGFDSIRKRMSVVIRHPLTDEINVYTKGADSVVMDLLLPCSSDDAR   800
 801  GRHQKKIRSKTQNYLNLYAVEGLRTLCIAKRVLSKEEYACWLQSHIEAEA   850
 851  SVESREELLFQSAVRLETNLHLLGATGIEDRLQEGVPETIAKLRQAGLQI   900
 901  WVLTGDKQETAINIAYACKLLDHGEEVITLNADSQEACAALLDQCLSYVQ   950
 951  SRNPRSTLQNSESNLSVGFSFNPVSTSTDASPSPSLVIDGRSLAYALEKS  1000
1001  LEDKFLFLAKQCRSVLCCRSTPLQKSMVVKLVRSKLKAMTLAIGDGANDV  1050
1051  SMIQVADVGVGISGQEGMQAVMASDFAVPRFRYLERLLIVHGHWCYSRLA  1100
1101  NMVLYFFYKNTMFVGLLFWFQFYCGFSASAMIDQWYLIFFNLLFSSLPQL  1150
1151  VTGVLDKDVPADMLLREPQLYKSGQNMEEYRPRAFWLNMVDAAFQSLVCF  1200
1201  FIPYLAYYDSDVDVFTWGTPVTAIALFTFLLHLGIETKTWTWLNWLACGF  1250
1251  STFLFFSVALIYNTSCATCYPPSNPYWTMQTLLGDPLFYLTCLIAPIAAL  1300
1301  LPRLFFKALQGSLFPTQLQLGRQLAKKPLNKFSDPKETFAQGQPPGHSET  1350
1351  ELSERKTMGPFETLPRDCASQASQFTQQLTCSPEASGEPSAVDTNMPLRE  1400
1401  NTLLEGLGSQASGSSMPRGAISEVCPGDSKRQSTSASQTARLSSLFHLPS  1450
1451  FGSLNWISSLSLASGLGSVLQLSGSSLQMDKQDGEFLSNPPQPEQDLHSF  1500
1501  QGQVTGYL                                            1508

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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