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

NucPred

Fetching P18168 from www.uniprot.org...

The NucPred score for your sequence is 0.76 (see score help below)

   1  MFRKHFRRKPATSSSLESTIESADSLGMSKKTATKRQRPRHRVPKIATLP    50
  51  STIRDCRSLKSACNLIALILILLVHKISAAGNFELEILEISNTNSHLLNG   100
 101  YCCGMPAELRATKTIGCSPCTTAFRLCLKEYQTTEQGASISTGCSFGNAT   150
 151  TKILGGSSFVLSDPGVGAIVLPFTFRWTKSFTLILQALDMYNTSYPDAER   200
 201  LIEETSYSGVILPSPEWKTLDHIGRNARITYRVRVQCAVTYYNTTCTTFC   250
 251  RPRDDQFGHYACGSEGQKLCLNGWQGVNCEEAICKAGCDPVHGKCDRPGE   300
 301  CECRPGWRGPLCNECMVYPGCKHGSCNGSAWKCVCDTNWGGILCDQDLNF   350
 351  CGTHEPCKHGGTCENTAPDKYRCTCAEGLSGEQCEIVEHPCATRPCRNGG   400
 401  TCTLKTSNRTQAQVYRTSHGRSNMGRPVRRSSSMRSLDHLRPEGQALNGS   450
 451  SSPGLVSLGSLQLQQQLAPDFTCDCAAGWTGPTCEINIDECAGGPCEHGG   500
 501  TCIDLIGGFRCECPPEWHGDVCQVDVNECEAPHSAGIAANALLTTTATAI   550
 551  IGSNLSSTALLAALTSAVASTSLAIGPCINAKECRNQPGSFACICKEGWG   600
 601  GVTCAENLDDCVGQCRNGATCIDLVNDYRCACASGFKGRDCETDIDECAT   650
 651  SPCRNGGECVDMVGKFNCICPLGYSGSLCEEAKENCTPSPCLEGHCLNTP   700
 701  EGYYCHCPPDRAGKHCEQLRPLCSQPPCNEGCFANVSLATSATTTTTTTT   750
 751  TATTTRKMAKPSGLPCSGHGSCEMSDVGTFCKCHVGHTGTFCEHNLNECS   800
 801  PNPCRNGGICLDGDGDFTCECMSGWTGKRCSERATGCYAGQCQNGGTCMP   850
 851  GAPDKALQPHCRCAPGWTGLFCAEAIDQCRGQPCHNGGTCESGAGWFRCV   900
 901  CAQGFSGPDCRINVNECSPQPCQGGATCIDGIGGYSCICPPGRHGLRCEI   950
 951  LLSDPKSACQNASNTISPYTALNRSQNWLDIALTGRTEDDENCNACVCEN  1000
1001  GTSRCTNLWCGLPNCYKVDPLSKSSNLSGVCKQHEVCVPALSETCLSSPC  1050
1051  NVRGDCRALEPSRRVAPPRLPAKSSCWPNQAVVNENCARLTILLALERVG  1100
1101  KGASVEGLCSLVRVLLAAQLIKKPASTFGQDPGMLMVLCDLKTGTNDTVE  1150
1151  LTVSSSKLNDPQLPVAVGLLGELLSFRQLNGIQRRKELELQHAKLAALTS  1200
1201  IVEVKLETARVADGSGHSLLIGVLCGVFIVLVGFSVFISLYWKQRLAYRT  1250
1251  SSGMNLTPSLDALRHEEEKSNNLQNEENLRRYTNPLKGSTSSLRAATGME  1300
1301  LSLNPAPELAASAASSSALHRSQPLFPPCDFERELDSSTGLKQAHKRSSQ  1350
1351  ILLHKTQNSDMRKNTVGSLDSPRKDFGKRSINCKSMPPSSGDEGSDVLAT  1400
1401  TVMV                                                1404

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.)

Go back to the NucPred Home Page.