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

NucPred

Fetching P55066 from www.uniprot.org...

The NucPred score for your sequence is 0.63 (see score help below)

   1  MGAGSVWASGLLLLWLLLLVAGDQDTQDTTATEKGLRMLKSGSGPVRAAL    50
  51  AELVALPCFFTLQPRLSSLRDIPRIKWTKVQTASGQRQDLPILVAKDNVV   100
 101  RVAKGWQGRVSLPAYPRHRANATLLLGPLRASDSGLYRCQVVKGIEDEQD   150
 151  LVTLEVTGVVFHYRAARDRYALTFAEAQEACRLSSATIAAPRHLQAAFED   200
 201  GFDNCDAGWLSDRTVRYPITQSRPGCYGDRSSLPGVRSYGRRDPQELYDV   250
 251  YCFARELGGEVFYVGPARRLTLAGARAQCQRQGAALASVGQLHLAWHEGL   300
 301  DQCDPGWLADGSVRYPIQTPRRRCGGPAPGVRTVYRFANRTGFPAPGARF   350
 351  DAYCFRAHHHTAQHGDSEIPSSGDEGEIVSAEGPPGRELKPSLGEQEVIA   400
 401  PDFQEPLMSSGEGEPPDLTWTQAPEETLGSTPGGPTLASWPSSEKWLFTG   450
 451  APSSMGVSSPSDMGVDMEATTPLGTQVAPTPTMRRGRFKGLNGRHFQQQG   500
 501  PEDQLPEVAEPSAQPPTLGATANHMRPSAATEASESDQSHSPWAILTNEV   550
 551  DEPGAGSLGSRSLPESLMWSPSLISPSVPSTESTPSPKPGAAEAPSVKSA   600
 601  IPHLPRLPSEPPAPSPGPSEALSAVSLQASSADGSPDFPIVAMLRAPKLW   650
 651  LLPRSTLVPNMTPVPLSPASPLPSWVPEEQAVRPVSLGAEDLETPFQTTI   700
 701  AAPVEASHRSPDADSIEIEGTSSMRATKHPISGPWASLDSSNVTMNPVPS   750
 751  DAGILGTESGVLDLPGSPTSGGQATVEKVLATWLPLPGQGLDPGSQSTPM   800
 801  EAHGVAVSMEPTVALEGGATEGPMEATREVVPSTADATWESESRSAISST   850
 851  HIAVTMARAQGMPTLTSTSSEGHPEPKGQMVAQESLEPLNTLPSHPWSSL   900
 901  VVPMDEVASVSSGEPTGLWDIPSTLIPVSLGLDESVLNVVAESPSVEGFW   950
 951  EEVASGQEDPTDPCENNPCLHGGTCHTNGTVYGCSCDQGYAGENCEIDID  1000
1001  DCLCSPCENGGTCIDEVNGFICLCLPSYGGSLCEKDTEGCDRGWHKFQGH  1050
1051  CYRYFAHRRAWEDAERDCRRRAGHLTSVHSPEEHKFINSFGHENSWIGLN  1100
1101  DRTVERDFQWTDNTGLQYENWREKQPDNFFAGGEDCVVMVAHESGRWNDV  1150
1151  PCNYNLPYVCKKGTVLCGPPPAVENASLVGVRKIKYNVHATVRYQCDEGF  1200
1201  SQHRVATIRCRNNGKWDRPQIMCIKPRRSHRMRRHHHHPHRHHKPRKEHR  1250
1251  KHKRHPAEDWEKDEGDFC                                  1268

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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