| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P43057 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MSTSQPSQQQNPEQVVNDIRQKIEKERKIIQGFNDVKRNTNNPEVIQKWK 50
51 SKIIESQSMIDYYQETMNKLTRQMQRLNTNSSSRTASRSSVISEYKPSYS 100
101 NFDLIKYECPSLGNKIQFMLQYLEFKLQVENKYSEANKKLSHLYLMDGDK 150
151 SSSNAAEGGRAESDQRIQLLEKALKKYQKFSINDHEFDRDYEIMDSTKHS 200
201 RKLLTGRLTVSITCIRDVDHIATALAKKRETVVVIKVDDLEKARTKPSKN 250
251 DNWNEEMVIDVDKSHEIELAVMDKQNGIYVPVAVNWFSLFDLAEEIRKKK 300
301 VAKDQGSSGWLPAANLPQTGGSGAGTGSSMTGGASYGATSPLPAHNDLRP 350
351 SVSPSSDAKENKVSVSTWLSLEPGGQMLINLNFEKSITNGKQFRGPLGRH 400
401 GAIRQKKEEVFEKHGHQFVQKQFYNIMSCALCGEFLRYTGYQCQDCKFLC 450
451 HKKCYQKVVTKCISKSGSDYDAAQLNHRIPHRFEPITNHGTKWCCHCGYI 500
501 LPWGKKNVRKCTECGVMCHAQCTHLVPDFCGMSLQMANEILATIESTKVS 550
551 PKKAQHQQSHAKPLPPKPPIESKPSMDSEETLHNEPSYKSLRPASVVHQD 600
601 TNFVSKLPTTVQNKYQEPVELPPQQQNQVVPSTRRRGHGSTDLSFETGYG 650
651 QQQHQHHRDVPQIVVEDHQHYNSNDNRDVEMEESKDEFDNFDYNNKYTEN 700
701 EILTDVQQDQVRSPFADQIQGVPETSHAKQQNQQVQQVQQQEELGHQRTH 750
751 SSGKSGKSKRRKRKVGLDDFQFLAVLGKGNFGKVMLAESRHTSKLCAIKV 800
801 LKKDFIVENDEAESVKSEKRVFLTANKEMHPFLLNLHCCFQTENRIYFVM 850
851 EYISGGDLMWHIQKNRFTAKRAKFYACEVLLGLKYFHDNGIVYRDLKLDN 900
901 ILLTTKGHIKIGDYGLCKEDMWHKSTTSTFCGTPEFMAPEIVAGKAYDRS 950
951 VDWWAFGVLLFQMLLCQSPFKGDDEDDIFNAIENDEVKYPINLSRQTVLV 1000
1001 LQALLTKDPSQRLGSGPKDAEEIMEHPYFHDVNFDDVLNCRIPAPYIPEV 1050
1051 QSEHDYSNFDKEFTSETPRLTPVETVLTSEMQEQFRGFSHISDNATI 1097
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
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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