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

NucPred

Fetching Q02989 from www.uniprot.org...

The NucPred score for your sequence is 0.31 (see score help below)

   1  ACSSPEVSIFHFFVYAGSFVKNFKKMKGSSAISKREMSRADQCKLLAYTA    50
  51  VGYETVGNVAADIASIEGANLVAAPVAAGGHLGKGLTDAAMIAMDCSSIP   100
 101  FEEIKEILNKEFKEMGRKLDKNTEALEHVSKLVSKTLSTVEKIRVEMREG   150
 151  FKLVIETIENIATKEIVFDINKIVQYFNNERENINSRQKEEFVAKLQEPA   200
 201  PGNFLLYLRNSRTSESGTLYSLLFRIIDQELAIPNNAGDNNAIQALYALF   250
 251  YGTETFISIMFYLVKQYSYLAEYHYQKGNLEEFNTNFDHMKIVFQDFKFS   300
 301  LIGINQNTKPLVDEVLNVLNNVKNKSFIRNVQNKLFYDLMKQTESLLELK   350
 351  KEIANMELPIIDETPRLSISISFKERSDDKPVDTPLLKWDKGKEVKYAIQ   400
 401  FEQDGKFSKISSWSKPVTVQHLACPFISVDKDRRNRLIFRQFGDQIPELV   450
 451  GTLRGSQVEFRDIHRDLYNAAQVPYAREALSISRTLIQNGANVSETFELG   500
 501  RGAIHAAASAGNYDVGELLLNKDINLLEKADKNGYTPLHIAADSNKNDFV   550
 551  MFLIGNNADVNVRTKSDLFTPLHLAARRDLTDVTQTLIDITEIDLNAQDK   600
 601  SGFTPLHLSISSTSETAAILIRNTNAVINIKSKVGLTPLHLATLQNNLSV   650
 651  SKLLAGKGAYLNDGDANGMTPLHYAAMTGNLEMVDFLLNQQYININAATK   700
 701  EKKWTPLHLAILFKKNDVAERLLSDENLNIRLETNGGINPLHLASATGNK   750
 751  QLVIELLAKNADVTRLTSKGFSALHLGIIGKNEEIPFFLVEKGANVNDKT   800
 801  NSGVTPLHFAAGLGKANIFRLLLSRGADIKAEDINSQMPIHEAVSNGHLE   850
 851  IVRILIEKDPSLMNVKNIRNEYPFYLAVEKRYKDIFDYFVSKDANVNEVD   900
 901  HNGNTLLHLFSSTGELEVVQFLMQNGANFRLKNNERKTFFDLAIENGRLN   950
 951  IVAFAVEKNKVNLQAAHRGKTILYHAICDSAKYDKIEIVKYFIEKLNESE  1000
1001  CNPLHEAAAYAHLDLVKYFVQERGINPAEFNEENQASPFCITIHGAPCGY  1050
1051  SLDCDTPDRLEVVEYLSDKIPDINGKCDVQENTPITVAIFANKVSILNYL  1100
1101  VGIGADPNQQVDGDPPLYIAARQGRFEIVRCLIEVHKVDINTRNKERFTA  1150
1151  LHAAARNDFMDVVKYLVRQGADVNAKGIDDLRPIDIAGEKAKAYLQSSRF  1200
1201  LRSGHSFQSNEIDSFGNTIHGISMSARTNDKLTQQISSKGTRSDSNSTEG  1250
1251  KMHSENVHVRSIDVNGALLLLDFMIRVFASKKTNFAPYGSRIKTRSAAEA  1300
1301  QAEALIMTERFENLLSGLIGDPIPDSIDFSNVHSKIYKAIMSGRRSVISE  1350
1351  MLCSFAEEYSKLNHESIKQLLSEFETLTTTKASEIHIEESVPYAPFEICE  1400
1401  LKVNSNVSQIK                                         1411

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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