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

NucPred

Fetching P34641 from www.uniprot.org...

The NucPred score for your sequence is 0.53 (see score help below)

   1  MDETDPVPDMSLLPDTVPVVVSGDGSAAGIQLCPALILGSPQALPGAIKH    50
  51  IYSRLAAAASEVDQGVPDLIISLISHGNSLSTKYMSSVENGLKSFLIGCG   100
 101  TWLISSGEVNDPMSRVASGALKNVLPQLEHQAEVLHILVNSDDMIASDTT   150
 151  NSKSVVDTSLNTLLLICRKEPNDSYETVASSIAKLRAATAVKLAHPPPAL   200
 201  LIGVPSEPMSPSTYGNSAAILLSPSNDKRPFPVAIFAGASKESLIELLFF   250
 251  VEHGIPVIILQDSCELCAILHSSHLLLETSNFDNDKFISWLRSQLYPLGL   300
 301  ADCYTLITKLLVSSNSGDVQLIEFIDSSQLSELSSVVVDRCLECYATTGE   350
 351  ERQVLLLAAKLNSPSVLSSMDVAAQLDEELLTMILCECITKDDQLHFLSS   400
 401  VLQLSPPIRVTSNMLIRMMHHADEHFFTTIVLCQCMGYSYIPSEIDPRFA   450
 451  NDIQKLVKKLSFGVDNLFDPNVFCNDSSHRDKHESIRILAIWSLLLHRPG   500
 501  IVKCLAAFADEPVAFSMVLSRIARSLGHESHDWHFYEKSLNTLSDSLSGS   550
 551  ATTLFDTVFSTSPAKAYQLLCQPMEYFYGFNMTQLAFHCNAREIIAHECC   600
 601  QRWVHRKLYGNLQAKNFPIFLPKWAKICISAVLIIPVKFWMLVRPRERTK   650
 651  QDTVSPTVALLDVGKFPQKQRAISTYSVISSRSEALTALTAPLSTAFGFN   700
 701  SALNGAESATPQSMVFPLNIEEIDKDPRPFGKKNRIRRAHAPTLSTFYST   750
 751  PIVKYWLSLLFRIVFICCLAYSVVLPGCGSNLWDTGMWVWSFFWWIENCF   800
 801  VLTARARKIPLSLMPWRVFDVFAFFVFLILLLVMKVFPVTPVLEVLGIDS   850
 851  IYSAKVVSAFFVLYVSYSTLFTYIPLSDIFGPMIVRVKLMLLRDFTNFLF   900
 901  MIALVMLSSAVAIQAVVFPDRPVTMEVFRKTLSWIWLSLFTTDLSNLSES   950
 951  ETCRKSFLGAPKRYCSSVGQYANPSCPSQSLPAYLIVIEYFVILKLLLWP  1000
1001  ILFAFFSKTAKNVDDEADKIWRFQLYSLAEDFRLRPPLPPPLTIFCLICS  1050
1051  ACCRFSNSFSGFFSDFDHPDFEARDKCRTTWKFGSIYRNPSVPFKRNEFV  1100
1101  NSFWRKLSMEQWKNTQQKAKISANKSELQELHNIHNHIRMMTLRDSYENS  1150
1151  GTRKASELQFFEKYPESNILKISVNMVSKPWTVLVPRYNPPFYCKPAEDF  1200
1201  PSDVQKYVDIATEQNVGELKRIWRSRQANDVTSSNDKCWKLSAAGFPLNP  1250
1251  NGRTGMAGRGNHPRFGANRRCYYVVLSGGVEAKCQVLVDSQKNIPNEWHL  1300
1301  ENSSKDEHLTSILKMIGISDSDAHMFSMRRLDSSIITADKRIPSNDTSPA  1350
1351  HLASEVAENENDTDNAWTEHDVWAISLRERRIITTIIGYSWLPTSAIRGT  1400
1401  VLPWQADLVFRAKTIYGL                                  1418

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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