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

NucPred

Fetching Q04637 from www.uniprot.org...

The NucPred score for your sequence is 0.93 (see score help below)

   1  MNKAPQSTGPPPAPSPGLPQPAFPPGQTAPVVFSTPQATQMNTPSQPRQH    50
  51  FYPSRAQPPSSAASRVQSAAPARPGPAAHVYPAGSQVMMIPSQISYPASQ   100
 101  GAYYIPGQGRSTYVVPTQQYPVQPGAPGFYPGASPTEFGTYAGAYYPAQG   150
 151  VQQFPTGVAPTPVLMNQPPQIAPKRERKTIRIRDPNQGGKDITEEIMSGA   200
 201  RTASTPTPPQTGGGLEPQANGETPQVAVIVRPDDRSQGAIIADRPGLPGP   250
 251  EHSPSESQPSSPSPTPSPSPVLEPGSEPNLAVLSIPGDTMTTIQMSVEES   300
 301  TPISRETGEPYRLSPEPTPLAEPILEVEVTLSKPVPESEFSSSPLQAPTP   350
 351  LASHTVEIHEPNGMVPSEDLEPEVESSPELAPPPACPSESPVPIAPTAQP   400
 401  EELLNGAPSPPAVDLSPVSEPEEQAKEVTASMAPPTIPSATPATAPSATS   450
 451  PAQEEEMEEEEEEEEGEAGEAGEAESEKGGEELLPPESTPIPANLSQNLE   500
 501  AAAATQVAVSVPKRRRKIKELNKKEAVGDLLDAFKEANPAVPEVENQPPA   550
 551  GSNPGPESEGSGVPPRPEEADETWDSKEDKIHNAENIQPGEQKYEYKSDQ   600
 601  WKPLNLEEKKRYDREFLLGFQFIFASMQKPEGLPHISDVVLDKANKTPLR   650
 651  PLDPTRLQGINCGPDFTPSFANLGRTTLSTRGPPRGGPGGELPRGPAGLG   700
 701  PRRSQQGPRKEPRKIIATVLMTEDIKLNKAEKAWKPSSKRTAADKDRGEE   750
 751  DADGSKTQDLFRRVRSILNKLTPQMFQQLMKQVTQLAIDTEERLKGVIDL   800
 801  IFEKAISEPNFSVAYANMCRCLMALKVPTTEKPTVTVNFRKLLLNRCQKE   850
 851  FEKDKDDDEVFEKKQKEMDEAATAEERGRLKEELEEARDIARRRSLGNIK   900
 901  FIGELFKLKMLTEAIMHDCVVKLLKNHDEESLECLCRLLTTIGKDLDFEK   950
 951  AKPRMDQYFNQMEKIIKEKKTSSRIRFMLQDVLDLRGSNWVPRRGDQGPK  1000
1001  TIDQIHKEAEMEEHREHIKVQQLMAKGSDKRRGGPPGPPISRGLPLVDDG  1050
1051  GWNTVPISKGSRPIDTSRLTKITKPGSIDSNNQLFAPGGRLSWGKGSSGG  1100
1101  SGAKPSDAASEAARPATSTLNRFSALQQAVPTESTDNRRVVQRSSLSRER  1150
1151  GEKAGDRGDRLERSERGGDRGDRLDRARTPATKRSFSKEVEERSRERPSQ  1200
1201  PEGLRKAASLTEDRDRGRDAVKREAALPPVSPLKAALSEEELEKKSKAII  1250
1251  EEYLHLNDMKEAVQCVQELASPSLLFIFVRHGVESTLERSAIAREHMGQL  1300
1301  LHQLLCAGHLSTAQYYQGLYEILELAEDMEIDIPHVWLYLAELVTPILQE  1350
1351  GGVPMGELFREITKPLRPLGKAASLLLEILGLLCKSMGPKKVGTLWREAG  1400
1401  LSWKEFLPEGQDIGAFVAEQKVEYTLGEESEAPGQRALPSEELNRQLEKL  1450
1451  LKEGSSNQRVFDWIEANLSEQQIVSNTLVRALMTAVCYSAIIFETPLRVD  1500
1501  VAVLKARAKLLQKYLCDEQKELQALYALQALVVTLEQPPNLLRMFFDALY  1550
1551  DEDVVKEDAFYSWESSKDPAEQQGKGVALKSVTAFFKWLREAEEESDHN   1599

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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