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

NucPred

Fetching O88322 from www.uniprot.org...

The NucPred score for your sequence is 0.29 (see score help below)

   1  MFRDPTAGWLTPPSPLSLLVMLLLLSRVGALRPDELFPYGESWGDQLLPE    50
  51  GDDESSAAVKLAIPLRFYDAQFSSLYVGTNGIISTQDFPRETQYVDDDFP   100
 101  TDFPAIAPFLADIDTSHSRGRILYREDTSGAVLSLAARYVRTGFPLSGSS   150
 151  FTPTHAFLATWEHVGAYEEVSRGAAPSGELNTFQAVLASDESDTYALFLY   200
 201  PANGLQFFGTRPKESYNVQLQLPARVGFCRGEADDLKREALYFSLTNTEQ   250
 251  SVKNLYQLSNLGIPGVWAFHIGSRFALDNVRPATVGGDPSTARSSALEHP   300
 301  FSHAAALESYTEDSFHYYDENEEDVEYPPVEPGEAPEGHSRIDVSFNSKA   350
 351  DPGLVDVGTSSPGSDRASPWPYPAPGNWPSYRETESASLDPQTKQGRPVG   400
 401  EGEVLDFRDPAELLDQMGTRAPAPPEADAALLTPVNEDLGGRNTQSYPEA   450
 451  GPVPSEPDVPVPPLEGEVLPHYPESGHVPPLRGGKYVIGLEDHVGSNDQV   500
 501  FTYNGANLETCEHSHGRCSQHAFCTDYTTGFCCHCQSRFYGNGKHCLPEG   550
 551  APHRVNGKVSGRLRVGHIPVHFTDVDLHAYIVGNDGRAYTAISHVPQPAA   600
 601  QALLPVLPIGGLFGWLFALEKPGSENGFSLTGATFVHDVEVTFHPGEERV   650
 651  RITQTAEGLDPENYLSIKTNIEGQVPFIPANFTAHITPYKEFYHYRDSVV   700
 701  TSSSSRSFSLTSGSINQTWSYHIDQNITYQACRHAPRHLAIPATQQLTVD   750
 751  RAFALYSEDEGVLRFAVTNQIGPVEVDSAPVGVNPCYDGSHTCDTTARCH   800
 801  PGTGVDYTCECTPGFQGDGRSCVDVNECATGFHRCGPNSVCVNLVGSYRC   850
 851  ECRSGYEFADDQHTCILIAPPPNPCLDGSHTCAPEGQARCIHHGGSSFSC   900
 901  ACLPGFIGTGHQCSDVDECAENRCHEAAICYNTPGSFSCRCQPGYRGDGF   950
 951  HCTSDTVPEDSISGLKPCEYQQRYAQTQHAYPGSRIHIPQCDDQGNFVPL  1000
1001  QCHGSTGFCWCVDRNGHEVPGTQTPPGSTPPHCGPPPEPTQRPRTVCERW  1050
1051  RESLLEHYGGTPRDDQYVPQCDDLGHFIPLQCHGKSDFCWCVDKDGRELQ  1100
1101  GTRSQPGTRPACIPTVAPPVVRPTPRPDVTPPSVGTFLLYAQGQQIGHLP  1150
1151  LNGSRLQKDAARTLLSLHGSIVVGIDYDCRERMVYWTDVAGRTISRASLE  1200
1201  AGAEPETIITSGLISPEGLAIDHFRRTMYWTDSGLDKIERAELDGSERKV  1250
1251  LFHTDLVNPRAITVDPIRGNLYWTDWNREAPKIETSSLDGENRRILINKD  1300
1301  IGLPNGLTFDPFSKLLCWADAGTKKLECTLPDGTGRRVIQNHLNYPFSIV  1350
1351  SYADHFYHTDWRRDGVISVNKDSGQFTDEFLPEQRSHLYGITAVYPYCPT  1400
1401  GRK                                                 1403

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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