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

NucPred

Fetching Q9UHC9 from www.uniprot.org...

The NucPred score for your sequence is 0.18 (see score help below)

   1  MAEAGLRGWLLWALLLRLAQSEPYTTIHQPGYCAFYDECGKNPELSGSLM    50
  51  TLSNVSCLSNTPARKITGDHLILLQKICPRLYTGPNTQACCSAKQLVSLE   100
 101  ASLSITKALLTRCPACSDNFVNLHCHNTCSPNQSLFINVTRVAQLGAGQL   150
 151  PAVVAYEAFYQHSFAEQSYDSCSRVRVPAAATLAVGTMCGVYGSALCNAQ   200
 201  RWLNFQGDTGNGLAPLDITFHLLEPGQAVGSGIQPLNEGVARCNESQGDD   250
 251  VATCSCQDCAASCPAIARPQALDSTFYLGQMPGSLVLIIILCSVFAVVTI   300
 301  LLVGFRVAPARDKSKMVDPKKGTSLSDKLSFSTHTLLGQFFQGWGTWVAS   350
 351  WPLTILVLSVIPVVALAAGLVFTELTTDPVELWSAPNSQARSEKAFHDQH   400
 401  FGPFFRTNQVILTAPNRSSYRYDSLLLGPKNFSGILDLDLLLELLELQER   450
 451  LRHLQVWSPEAQRNISLQDICYAPLNPDNTSLYDCCINSLLQYFQNNRTL   500
 501  LLLTANQTLMGQTSQVDWKDHFLYCANAPLTFKDGTALALSCMADYGAPV   550
 551  FPFLAIGGYKGKDYSEAEALIMTFSLNNYPAGDPRLAQAKLWEEAFLEEM   600
 601  RAFQRRMAGMFQVTFMAERSLEDEINRTTAEDLPIFATSYIVIFLYISLA   650
 651  LGSYSSWSRVMVDSKATLGLGGVAVVLGAVMAAMGFFSYLGIRSSLVILQ   700
 701  VVPFLVLSVGADNIFIFVLEYQRLPRRPGEPREVHIGRALGRVAPSMLLC   750
 751  SLSEAICFFLGALTPMPAVRTFALTSGLAVILDFLLQMSAFVALLSLDSK   800
 801  RQEASRLDVCCCVKPQELPPPGQGEGLLLGFFQKAYAPFLLHWITRGVVL   850
 851  LLFLALFGVSLYSMCHISVGLDQELALPKDSYLLDYFLFLNRYFEVGAPV   900
 901  YFVTTLGYNFSSEAGMNAICSSAGCNNFSFTQKIQYATEFPEQSYLAIPA   950
 951  SSWVDDFIDWLTPSSCCRLYISGPNKDKFCPSTVNSLNCLKNCMSITMGS  1000
1001  VRPSVEQFHKYLPWFLNDRPNIKCPKGGLAAYSTSVNLTSDGQVLDTVAI  1050
1051  LSPRLEYSGTISAHCNLYLLDSTSRFMAYHKPLKNSQDYTEALRAARELA  1100
1101  ANITADLRKVPGTDPAFEVFPYTITNVFYEQYLTILPEGLFMLSLCLVPT  1150
1151  FAVSCLLLGLDLRSGLLNLLSIVMILVDTVGFMALWGISYNAVSLINLVS  1200
1201  AVGMSVEFVSHITRSFAISTKPTWLERAKEATISMGSAVFAGVAMTNLPG  1250
1251  ILVLGLAKAQLIQIFFFRLNLLITLLGLLHGLVFLPVILSYVGPDVNPAL  1300
1301  ALEQKRAEEAVAAVMVASCPNHPSRVSTADNIYVNHSFEGSIKGAGAISN  1350
1351  FLPNNGRQF                                           1359

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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