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

NucPred

Fetching Q924C1 from www.uniprot.org...

The NucPred score for your sequence is 0.75 (see score help below)

   1  MEMEQVNALCEELVKAVTVMMDPSSTQRYRLEALKFCEEFKEKCPICVPC    50
  51  GLKLAEKTQIAIVRHFGLQILEHVVKFRWNSMSRLEKVYLKNSVMELIAN   100
 101  GTLRILEEENHIKDVLSRIVVEMIKREWPQHWPDMLMELDTLFRQGETQR   150
 151  ELVMFILLRLAEDVVTFQTLPTQRRRDIQQTLTQNMERILNFLLNTLQEN   200
 201  VNKYQQMKTDSSQEAEAQANCRVSVAALNTLAGYIDWVSLNHITAENCKL   250
 251  VETLCLLLNEQELQLGAAECLLIAVSRKGKLEDRKRLMILFGDVAMHYIL   300
 301  SAAQTADGGGLVEKHYLFLKRLCQVLCALGNLLCALLALDANIQTPINFG   350
 351  MYLESFLAFTTHPSQFLRSSTHMTWGALFRHEVLSRDPALLAVIPKYLRA   400
 401  SMTNLVKMGFPSKTDSPSCEYSRFDFDSDEDFNAFFNSSRAQHGEVVRCV   450
 451  CRLDPKTSFQMAAEWLKYQLSASIDTGPVNSCSTAGTGEGGFCSIFSPSY   500
 501  VQWEAMTFFLESVINQMFRTLDKEELPVSDGIELLQLVLNFEIKDPLVLS   550
 551  CVLTNVSALFPFVTYKPAFLPQVFSKLFSFVTFESVGESKAPRTRAVRNV   600
 601  RRHACSSINKMCRDYPDLVLPNFDMLYSHVKQLLSNELLLTQMEKCALME   650
 651  ALVLVSNQFKDYERQKLFLEELMAPVVNIWLSEEMCRALSDIDSFIAYVG   700
 701  ADLKSCDPAVEDPCGLNRARMSFCVYSILGVMRRTSWPSDLEEAKAGGFV   750
 751  VGYTPSGNPIFRNPCTEQILRLLDNLLALVRTHNTLYTPEMLTKMAEPFT   800
 801  KALDIVESEKTAILGLPQPLLEFNDHPVYRTTLERMQRFFGILYENCYHI   850
 851  LGKAGPSMQQDFYTVEDLASQLLGSAFVNLNNIPDFRLRSMLRVFVKPLV   900
 901  LFCPSEHYETLISPILGPLFTYLHMRLSQKWHVINQRSILCGEDEIAEDN   950
 951  PESQEMLEEQLVRMLTREAMDLIMACCVSKKTADHTAAPTADGDDEEMMA  1000
1001  TEVAPSSVVELTDLGKCLMKHEDVCTALLITAFNSLTWKDTLSCQRATTQ  1050
1051  LCWPLLKQVMSGTLLADAVTWLFTSVLKGLQMHGQHDGCMASLVHLAFQI  1100
1101  YEALRPRYLEIRAVMEQIPEINKESLDQFDCKLLNPSLQKAADKRRKDHF  1150
1151  KRLIAGCIGKPLGEQFRKEVHIKNLPWLFKKPKPMLETEVLDSEEGGLAT  1200
1201  IFEP                                                1204

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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