 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q00804 from www.uniprot.org...
The NucPred score for your sequence is 0.19 (see score help below)
1 MGDMANNSVVYGGVKNSLKEANHDGDFGITLAAVRALMELRSTDALRKIL 50
51 ESYGDVYGICTKLKTSPNEGLRGNPADLERREAVFGKNFIPPKKPKTFLQ 100
101 LVWEALQDVTLIILEIAAIVSLGLSFYQPPEGDNALCGEVSVGEEEGEGE 150
151 TGWIEGAAILLSVVCVVLVTAFNDWSKEKQFRGLQSRIEQEQKFTVIRGG 200
201 QVIQIPVSDITVGDIAQVKYGDLLPADGILIQGNDLKIDESSLTGESDHV 250
251 KKSLDKDPLLLSGTHVMEGSGRMVVTAVGVNSQTGIIFTLLGAGGEEEEK 300
301 KDEKKKEKKNKKQDGAIENRNKAKAQDGEPMEMQPLKSEEGGDGDEKDKK 350
351 KANLPKKEKSVLQGKLTKLAVQIGKAGLLMSAITVIILVLYFLIDTFWVQ 400
401 KRPWLAECTPIYIQYFVKFFIIGVTVLVVAVPEGLPLPVTISLAYSVNEM 450
451 MKDNNLVRHLDACETMGNATAICSDKTGTLTMNRMAVVQAYINEKHYKKV 500
501 PEPEPYPPNILSYLVTGISVNCAYTSKILPPEEEGGLPRIVGNKTECALL 550
551 GPLLDLKQDYQDVRNEIPEEALYKVYTFQSVRKSMSTVLKNSDGSFRIFS 600
601 KGASEIILKKCFKILSANGEAKVFRPRDRDDIVKTVIEPMASEGLRTICL 650
651 AFRDFPAGEPEPEWDNENDIVTGLTCIAVVGIEDPGRPEVADAIKKCQRA 700
701 GITVEVVTGDNINTARAIATKCGILHPGEDFLCLEGKDFNRRIRNEKGEI 750
751 EQESIDKIWPKLRVLARSSPTDKHTLVKGIIDSTVSEQRQVVAVTGDGTN 800
801 DGPALKKADGGFAMGIAGTDVAKEASDIILTDDNFTSIVKAVMWGRNVYD 850
851 SISKFLQFQLTVNVVAVIVAFTGACITQDSPLKAVQMLWVNLIMDTLASL 900
901 ALATEPPTESLLLGKPYGRNKPLISRTMMKNILGHAFYQLVVVFTLLLAG 950
951 EKFFDIDSGRNAPLHAPPSEHYTIVFNIFVLMQLFNEINARKIHGERNVF 1000
1001 EGIFNNAIFCTIVLGTFVVQIIIVQFAGKPFSCSELSVEQWLWSIFLGMG 1050
1051 TLLWGQLISTIPTSRLKFQKEVVHGTQKREIGEEELAEDVEEIVHAEREL 1100
1101 RRWQILWFRGLNRIQTQIRVVNAFRSSLYEGLEKPESRSSIHNFMTHPEF 1150
1151 RIEDSEPHIPLIDDTDAEDDAPTKRNSSPPPSPNKNNNLVDSGIHLTIEM 1200
1201 NKSATSSSPGSPLHSLETSL 1220
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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