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  MYKMFRKHFRRKPATSSSLESTIESADSLGMSKKTATKRQRPRHRVPKIA    50
  51  TLPSTIRDCRSLKSACNLIALILILLVHKISAAGNFELEILEISNTNSHL   100
 101  LNGYCCGMPAELRATKTIGCSPCTTAFRLCLKEYQTTEQGASISTGCSFG   150
 151  NATTKILGGSSFVLSDPGVGAIVLPFTFRWTKSFTLILQALDMYNTSYPD   200
 201  AERLIEETSYSGVILPSPEWKTLDHIGRNARITYRVRVQCAVTYYNTTCT   250
 251  TFCRPRDDQFGHYACGSEGQKLCLNGWQGVNCEEAICKAGCDPVHGKCDR   300
 301  PGECECRPGWRGPLCNECMVYPGCKHGSCNGSAWKCVCDTNWGGILCDQD   350
 351  LNFCGTHEPCKHGGTCENTAPDKYRCTCAEGLSGEQCEIVEHPCATRPCR   400
 401  NGGTCTLKTSNRTQAQVYRTSHGRSNMGRPVRRSSSMRSLDHLRPEGQAL   450
 451  NGSSSPGLVSLGSLQLQQQLAPDFTCDCAAGWTGPTCEINIDECAGGPCE   500
 501  HGGTCIDLIGGFRCECPPEWHGDVCQVDVNECEAPHSAGIAANALLTTTA   550
 551  TAIIGSNLSSTALLAALTSAVASTSLAIGPCINAKECRNQPGSFACICKE   600
 601  GWGGVTCAENLDDCVGQCRNGATCIDLVNDYRCACASGFKGRDCETDIDE   650
 651  CATSPCRNGGECVDMVGKFNCICPLGYSGSLCEEAKENCTPSPCLEGHCL   700
 701  NTPEGYYCHCPPDRAGKHCEQLRPLCSQPPCNEGCFANVSLATSATTTTT   750
 751  TTTTATTTRKMAKPSGLPCSGHGSCEMSDVGTFCKCHVGHTGTFCEHNLN   800
 801  ECSPNPCRNGGICLDGDGDFTCECMSGWTGKRCSERATGCYAGQCQNGGT   850
 851  CMPGAPDKALQPHCRCAPGWTGLFCAEAIDQCRGQPCHNGGTCESGAGWF   900
 901  RCVCAQGFSGPDCRINVNECSPQPCQGGATCIDGIGGYSCICPPGRHGLR   950
 951  CEILLSDPKSACQNASNTISPYTALNRSQNWLDIALTGRTEDDENCNACV  1000
1001  CENGTSRCTNLWCGLPNCYKVDPLSKSSNLSGVCKQHEVCVPALSETCLS  1050
1051  SPCNVRGDCRALEPSRRVAPPRLPAKSSCWPNQAVVNENCARLTILLALE  1100
1101  RVGKGASVEGLCSLVRVLLAAQLIKKPASTFGQDPGMLMVLCDLKTGTND  1150
1151  TVELTVSSSKLNDPQLPVAVGLLGELLSFRQLNGIQRRKELELQHAKLAA  1200
1201  LTSIVEVKLETARVADGSGHSLLIGVLCGVFIVLVGFSVFISLYWKQRLA  1250
1251  YRTSSGMNLTPSLDALRHEEEKSNNLQNEENLRRYTNPLKGSTSSLRAAT  1300
1301  GMELSLNPAPELAASAASSSALHRSQPLFPPCDFERELDSSTGLKQAHKR  1350
1351  SSQILLHKTQNSDMRKNTVGSLDSPRKDFGKRSINCKSMPPSSGDEGSDV  1400
1401  LATTVMV                                             1407

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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