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

NucPred

Fetching Q9Z0W3 from www.uniprot.org...

The NucPred score for your sequence is 0.41 (see score help below)

   1  MAAAGSLERSFVELSGAERERPRHFREFTVCDIGTASAAFGTVKYSESAG    50
  51  GFYYVESGKLFSITRNRFIHWKTSGDTLELVEESLDLNLLNNAVRLKFQN   100
 101  YNILPGGVHVSETQNHVIILILTNQTVHRLILPHPSRMYRSELVTESQMQ   150
 151  SIFTDIGKVDFRDPCNSQLIPSVPGLSPGSTTSAAWLSSDGEALFALPSA   200
 201  SGGIFVLKLPPYDVPGIASVVELKQSSVMQRLLTGWMPTAIRGDHGPSDR   250
 251  ALSLAVHCVEHDAFIFALCQDHKLRMWSYKDQMCLMVADMLEYVPVNKDL   300
 301  RLTAGTGHKLRLAYSPSMGLYLGIYMHAPKRGQFCVFQLVSTENNRYSLD   350
 351  HISSLFTSQETLVDFALTSTDIWALWHDAENQTIVKYINFEHNVAGQWNP   400
 401  VFMQPLPEEEIVIRDDQDPREMYLRSLFTPGHFINAALCKALQIFCRGTE   450
 451  RNLDLSWNELKKEITLAVENELQGSVTEYEFSQDEFRTLQQEFWCKFYAC   500
 501  VLQYQEALSHPLALHLNPVTNMVCLLKKGYLSFLVPSSLVDHLYLLPDEH   550
 551  LLTEDETTISDDADVARDVLCLIKCLRMIGESVTMDMAVLMETSCYNLQS   600
 601  PEKAAEHILEDLITIDVENVMEDICSKLQEIRNPVHAIGLLIREMDYETE   650
 651  VEMEKGFDPAQPLNVRMNLSQLYGSSTAGYIVCRGVYKIASTRFLICRDL   700
 701  LILQQLLTRLGDAVILGAGQLFQAQQDLLHRTAPLLLSYYLIKWASQCLA   750
 751  TDVPVDTLESNLQHLSVLELTDSGALMANKLVSSPQTIMELFFQEVARKQ   800
 801  IISHLFSQPKAPLSQTGLNWPEMITAVTGYLLQLLWPSNPGCLFLECLMG   850
 851  NCQYVQLQDYIQLLHPWCQVNVGSCRFMLGRCYLVTGEVQKALECFCQAA   900
 901  SEVGKEEFLDRLIRSEDGEIVSTPKLQYYDKVLRLLDVVGLPELVIQLAT   950
 951  SAITEAGDDWKSQATLRTCIFKHHLDLGHNSQAYEALTQIPDSSRQLDCL  1000
1001  RQLVVVLCERSQLQDLVEFPYVNLHNEVVGIIESRARAVDLMTHNYYELL  1050
1051  YAFHIYRHNYRKAGTVMFEYGMRLGREVRTLRGLEKQGNCYLAAINCLRL  1100
1101  IRPEYAWIVQPASGAVSDRPGASPKRNHDGECTAAPTNRQIEILELEDLE  1150
1151  KEYSLARIRLTLARHDPSVIAIAGSSSAKEMSALLVQAGLFDTAISLCQT  1200
1201  FTLPLTPVFEGLAFKCIKLQFGGEAAQGEAWSWLATNQLSSVITTKESSA  1250
1251  TDEAWRLLSTYLERYKVQNNLYHHCVINKLLSHGVPLPNWLINSYKKVDA  1300
1301  AELLRLYLNYDLLEEAVDLVSEYVDAVLGKGHQYFGIEFPLSATAPMVWL  1350
1351  PYSSIDQLLQALGENSANSHNIILSQKILDKLEDYQQKVDKATRDLLYRR  1400
1401  DL                                                  1402

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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