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

NucPred

Fetching Q00808 from www.uniprot.org...

The NucPred score for your sequence is 0.40 (see score help below)

   1  MRLLERDDAGEIRPTKDLPSGKIPPYAILSHTWGPDEEEVSYKDLKDGRA    50
  51  VSKLGYNKIRFCADQAWRDGRKFFWVDTCCIDKSNSTELQEAINSMFRWY   100
 101  RDAAKCYVYLTDVSTDKRDADGDPSWKWAFQKCKWFTRGWTLQELIAPTS   150
 151  VEFFSREKARIGDRNSLERMIHDVTGIPLEALRGSPLSDFSVHDRMAWMK   200
 201  QRNTTREEDMAYSLFGIFDVHLPLIYGEGKEKALERLREKIGKDDGCLAD   250
 251  LRVTDPRHDKKRIEAAKGGLLKDSYCWVLSNVQFQQWHDGDDQRLLWING   300
 301  DPGKGKTMLLCGIIDELKKSTPPGLLSFFFCQATDSRINNATAVLRGLIY   350
 351  LLVSQQPALISHVRRPYDHAGKKMFEGPNVWIVLCEIFTSILQDPGLRMT   400
 401  YLIIDALDECVTDLPQLLELITRTSCTSSPIKWIVSSRNWPDIEEQLETA   450
 451  TQKARLSLELNAESISTAVNAFIQNRIDQLAPKTKHDANMIGKIRDYLHS   500
 501  HANGTFLWVALVCQALADPKVKKRHILAKLQTFPRGLDSLYARMLEQIGH   550
 551  SEDAELCKQILAVAAAVRRPISLDELASLVEMPDDVSDDPESLEEIVKLC   600
 601  GSFLIIRERTVYFVHQSAKDFLLGTASDKASNKASQEAFELVFPTGIEDV   650
 651  SYIIFWRSLNVMSQKLRRDIYCLNAPGFLIDNVRVPDPDPLATVRYSCIY   700
 701  WIDHLRDLVSSTSSKWVHLLQDDGDIHRFLTTKYLYWLEALSLLRALPEG   750
 751  INAIRQLESLLGHTIRGRLIAIVRDGYRFALSYRMIIEKAPLQAYTSALV   800
 801  FAPTDSMIKKIFKKEEPGWISTISVVEAEWNACTQTLEGHGSSVLSVAFS   850
 851  ADGQRVASGSDDKTIKIWDTASGTGTQTLEGHGGSVWSVAFSPDRERVAS   900
 901  GSDDKTIKIWDAASGTCTQTLEGHGGRVQSVAFSPDGQRVASGSDDHTIK   950
 951  IWDAASGTCTQTLEGHGSSVLSVAFSPDGQRVASGSGDKTIKIWDTASGT  1000
1001  CTQTLEGHGGSVWSVAFSPDGQRVASGSDDKTIKIWDTASGTCTQTLEGH  1050
1051  GGWVQSVVFSPDGQRVASGSDDHTIKIWDAVSGTCTQTLEGHGDSVWSVA  1100
1101  FSPDGQRVASGSIDGTIKIWDAASGTCTQTLEGHGGWVHSVAFSPDGQRV  1150
1151  ASGSIDGTIKIWDAASGTCTQTLEGHGGWVQSVAFSPDGQRVASGSSDKT  1200
1201  IKIWDTASGTCTQTLEGHGGWVQSVAFSPDGQRVASGSSDNTIKIWDTAS  1250
1251  GTCTQTLNVGSTATCLSFDYTNAYINTNIGRIQIATATMESLNQLSSPVC  1300
1301  YSYGLGQDHRWITCNNQNVLWLPPEYHTSAFTMQGRKIVLGSYSGRIIIF  1350
1351  LFSRDV                                              1356

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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