 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P16234 from www.uniprot.org...
The NucPred score for your sequence is 0.17 (see score help below)
1 MGTSHPAFLVLGCLLTGLSLILCQLSLPSILPNENEKVVQLNSSFSLRCF 50
51 GESEVSWQYPMSEEESSDVEIRNEENNSGLFVTVLEVSSASAAHTGLYTC 100
101 YYNHTQTEENELEGRHIYIYVPDPDVAFVPLGMTDYLVIVEDDDSAIIPC 150
151 RTTDPETPVTLHNSEGVVPASYDSRQGFNGTFTVGPYICEATVKGKKFQT 200
201 IPFNVYALKATSELDLEMEALKTVYKSGETIVVTCAVFNNEVVDLQWTYP 250
251 GEVKGKGITMLEEIKVPSIKLVYTLTVPEATVKDSGDYECAARQATREVK 300
301 EMKKVTISVHEKGFIEIKPTFSQLEAVNLHEVKHFVVEVRAYPPPRISWL 350
351 KNNLTLIENLTEITTDVEKIQEIRYRSKLKLIRAKEEDSGHYTIVAQNED 400
401 AVKSYTFELLTQVPSSILDLVDDHHGSTGGQTVRCTAEGTPLPDIEWMIC 450
451 KDIKKCNNETSWTILANNVSNIITEIHSRDRSTVEGRVTFAKVEETIAVR 500
501 CLAKNLLGAENRELKLVAPTLRSELTVAAAVLVLLVIVIISLIVLVVIWK 550
551 QKPRYEIRWRVIESISPDGHEYIYVDPMQLPYDSRWEFPRDGLVLGRVLG 600
601 SGAFGKVVEGTAYGLSRSQPVMKVAVKMLKPTARSSEKQALMSELKIMTH 650
651 LGPHLNIVNLLGACTKSGPIYIITEYCFYGDLVNYLHKNRDSFLSHHPEK 700
701 PKKELDIFGLNPADESTRSYVILSFENNGDYMDMKQADTTQYVPMLERKE 750
751 VSKYSDIQRSLYDRPASYKKKSMLDSEVKNLLSDDNSEGLTLLDLLSFTY 800
801 QVARGMEFLASKNCVHRDLAARNVLLAQGKIVKICDFGLARDIMHDSNYV 850
851 SKGSTFLPVKWMAPESIFDNLYTTLSDVWSYGILLWEIFSLGGTPYPGMM 900
901 VDSTFYNKIKSGYRMAKPDHATSEVYEIMVKCWNSEPEKRPSFYHLSEIV 950
951 ENLLPGQYKKSYEKIHLDFLKSDHPAVARMRVDSDNAYIGVTYKNEEDKL 1000
1001 KDWEGGLDEQRLSADSGYIIPLPDIDPVPEEEDLGKRNRHSSQTSEESAI 1050
1051 ETGSSSSTFIKREDETIEDIDMMDDIGIDSSDLVEDSFL 1089
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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