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

NucPred

Fetching P52593 from www.uniprot.org...

The NucPred score for your sequence is 0.84 (see score help below)

   1  MATPSFGNSSPQLTFTHVANFMNDAAADVSAVDAKQLAQIRQFLKANKTN    50
  51  LIESLNTIRQNVTSSGDHNKLRSTIANLLQINVDNDPFFAQSEDLSHAVE   100
 101  FFMSERSSRLHIVYSLLVNPDIDLETYSFIDNDRFNVVGKLISIISSVIQ   150
 151  NYDIITASSLAHDYNNDQDMFTIVSLVQLKKFSDLKFILQILQILNLMIL   200
 201  NTKVPVDIVNQWFLQYQNQFVEFCRNINSTDKSIDTSSLQLYKFQNFQDL   250
 251  SYLSETLISRISSLFTITTILILGLNTSIAQFDIQSPLYMDTETFDTVNS   300
 301  ALENDVATNIVNEDPIFHPMIHYSWSFILYYRRALQSSESFDDSDITKFA   350
 351  LFAESHDVLQKLNTLSEILSFDPVYTTVITVFLEFSLNFIPITASTSRVF   400
 401  AKIISKAPEQFIENFLTNDTFEKKLSIIKAKLPLLNESLIPLINLALIDT   450
 451  EFANFELKDICSFAVTKSSLNDLDYDLIADTITNSSSSSDIIVPDLIELK   500
 501  SDLLVAPPLENENSNCLLSIPKSTKGKILTIKQQQQQQQQQNGQQPPTTS   550
 551  NLIIFLYKFNGWSLVGRILQNLLHSYMEKGTQLDDLQHELMISIIKLVTN   600
 601  VVDPKTSIEKSSEILSYLSNSLDTSASTINGASIIQVIFEIFEISLQRKD   650
 651  YTSIVQCCEFMTMLTPNYLHLVSSYLNKSDLLDKYGKTGLSNMILGSVEL   700
 701  STGDYTFTIQLLKLTKVFIRESLSLKNIHISKRSKIDIINKLILHAIHIF   750
 751  ESYYNWKYNNFLQKFEIAFHLTLIFYDVLHDVFTINPHQKDQLIISSSAN   800
 801  KLLQLFLTPMDSIDLAPNTLTNILISPLNTTTKILGDKILGNLYSKVMNN   850
 851  SFKLCTLLIAIRGSNRDLKPSNLEKLLFINSSKLVDVYTLPSYVHFKVQI   900
 901  IELLSYLVEAPWNDDYPFLLSFLGEAKSMAFLKEVLSDLSSPVQDWNLLR   950
 951  SLYIFFTTLLESKQDGLSILFLTGQFASNKKINDESSIDKKSSILTVLQK  1000
1001  NSLLLDSTPEEVSCKLLETITYVLNTWTNSKIFIKDPKFVNSLLAKLKDS  1050
1051  KKLFQKKENLTRDETVSLIKKYKLISRIVEIFALCIYNSTDSNSEILNFL  1100
1101  NQEDLFELVHHFFQIDGFNKTFHDELNLKFKEKWPSLELQSFQKIPLSRI  1150
1151  NENENFGYDIPLLDIVLKADRSWNEPSKSQTNFKEEITDASLNLQYVNYE  1200
1201  ISTAKAWGALITTFVKRSTVPLNDGFVDLVEHFLKLNIDFGSDKQMFTQI  1250
1251  YLERIELSFYILYSFKLSGKLLKEEKIIELMNKIFTIFKSGEIDFIKNIG  1300
1301  KSLKNNFYRPLLRSVLVLLELVSSGDRFIELISDQLLEFFELVFSKGVYL  1350
1351  ILSEILCQINKCSTRGLSTDHTTQIVNLEDNTQDLLLLLSLFKKITNVNP  1400
1401  SKNFNVILASSLNEVGTLKVILNLYSSAHLIRINDEPILGQITLTFISEL  1450
1451  CSIEPIAAKLINSGLYSVLLESPLSVAIQQGDIKPEFSPRLHNIWSNGLL  1500
1501  SIVLLLLSQFGIKVLPETCLFVSYFGKQIKSTIYNWGDNKLAVSSSLIKE  1550
1551  TNQLVLLQKMLNLLNYQELFIQPKNSDDQQEAVELVIGLDSEHDKKRLSA  1600
1601  ALSKFLTHPKYLNSRIIPTTLEEQQQLEDESSRLEFVKGISRDIKALQDS  1650
1651  LFKDV                                               1655

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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