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

NucPred

Fetching Q80V62 from www.uniprot.org...

The NucPred score for your sequence is 0.78 (see score help below)

   1  MISKRRRLDSEDKENLTEDASKTMPLSKLAKKSHNSHEVEENGSVFVKLL    50
  51  KASGLTLKTGENQNQLGVDQVIFQRKLFQALRKHPAYPKVIEEFVNGLES   100
 101  YTEDSESLRNCLLSCERLQDEEASMGTFYSKSLIKLLLGIDILQPAIIKM   150
 151  LFEKVPQFLFESENRDGINMARLIINQLKWLDRIVDGKDLTAQMMQLISV   200
 201  APVNLQHDFITSLPEILGDSQHANVGKELGELLVQNTSLTVPILDVFSSL   250
 251  RLDPNFLSKIRQLVMGKLSSVRLEDFPVIVKFLLHSVTDTTSLEVIAELR   300
 301  ENLNVQQFILPSRIQASQSKLKSKGLASSSGNQENSDKDCIVLVFDVIKS   350
 351  AIRYEKTISEAWFKAIERIESAAEHKALDVVMLLIIYSTSTQTKKGVEKL   400
 401  LRNKIQSDCIQEQLLDSAFSTHYLVLKDICPSILLLAQTLFHSQDQRIIL   450
 451  FGSLLYKYAFKFFDTYCQQEVVGALVTHVCSGTEAEVDTALDVLLELIVL   500
 501  NASAMRLNAAFVKGILDYLENMSPQQIRKIFCILSTLAFSQQPGTSNHIQ   550
 551  DDMHLVIRKQLSSTVFKYKLIGIIGAVTMAGIMAEDRSVPSNSSQRSANV   600
 601  SSEQRTQVTSLLQLVHSCTEHSPWASSLYYDEFANLIQERKLAPKTLEWV   650
 651  GQTIFNDFQDAFVVDFCAAPEGDFPFPVKALYGLEEYSTQDGIVINLLPL   700
 701  FYQECAKDASRATSQESSQRSMSSLCLASHFRLLRLCVARQHDGNLDEID   750
 751  GLLDCPLFLPDLEPGEKLESMSAKDRSLMCSLTFLTFNWFREVVNAFCQQ   800
 801  TSPEMKGKVLSRLKDLVELQGILEKYLAVIPDYVPPFASVDLDTLDMMPR   850
 851  SSSAVAAKNRNKGKTGGKKQKADSNKASCSDTLLTEDTSECDMAPSGRSH   900
 901  VDKESTGKEGKTFVSLQNYRAFFRELDIEVFSILHSGLVTKFILDTEMHT   950
 951  EATEVVQLGPAELLFLLEDLSQKLENMLTAPFAKRICCFKNKGRQNIGFS  1000
1001  HLHQRSVQDIVHCVVQLLTPMCNHLENIHNFFQCLGAEHLSADDKARATA  1050
1051  QEQHTMACCYQKLLQVLHALFAWKGFTHQSKHRLLHSALEVLSNRLKQME  1100
1101  QDQPLEELVSQSFSYLQNFHHSVPSFQCGLYLLRLLMALLEKSAVPNQKK  1150
1151  EKLASLAKQLLCRAWPHGEKEKNPTFNDHLHDVLYIYLEHTDNVLKAIEE  1200
1201  ITGVGVPELVSAPKDAASSTFPTLTRHTFVIFFRVMMAELEKTVKGLQAG  1250
1251  TAADSQQVHEEKLLYWNMAVRDFSILLNLMKVFDSYPVLHVCLKYGRRFV  1300
1301  EAFLKQCMPLLDFSFRKHREDVLSLLQTLQLNTRLLHHLCGHSKIRQDTR  1350
1351  LTKHVPLLKKSLELLVCRVKAMLVLNNCREAFWLGTLKNRDLQGEEIISQ  1400
1401  DPSSSESNAEDSEDGVTSHVSRNRATEDGEDEASDEQKDQDSDESDDSSS  1450

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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