 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9M0V3 from www.uniprot.org...
The NucPred score for your sequence is 0.16 (see score help below)
1 MSSWNYVVTAHKPTSVTHSCVGNFTSPQELNLIVAKCTRIEIHLLTPQGL 50
51 QPMLDVPIYGRIATLELFRPHGEAQDFLFIATERYKFCVLQWDPESSELI 100
101 TRAMGDVSDRIGRPTDNGQIGIIDPDCRLIGLHLYDGLFKVIPFDNKGQL 150
151 KEAFNIRLEELQVLDIKFLFGCAKPTIAVLYQDNKDARHVKTYEVSLKDK 200
201 DFVEGPWSQNSLDNGADLLIPVPPPLCGVLIIGEETIVYCSASAFKAIPI 250
251 RPSITKAYGRVDVDGSRYLLGDHAGMIHLLVITHEKEKVTGLKIELLGET 300
301 SIASTISYLDNAVVFVGSSYGDSQLVKLNLHPDAKGSYVEVLERYINLGP 350
351 IVDFCVVDLERQGQGQVVTCSGAFKDGSLRVVRNGIGINEQASVELQGIK 400
401 GMWSLKSSIDEAFDTFLVVSFISETRILAMNLEDELEETEIEGFLSQVQT 450
451 LFCHDAVYNQLVQVTSNSVRLVSSTTRELRDEWHAPAGFTVNVATANASQ 500
501 VLLATGGGHLVYLEIGDGKLTEVQHALLEYEVSCLDINPIGDNPNYSQLA 550
551 AVGMWTDISVRIFSLPELTLITKEQLGGEIIPRSVLLCAFEGISYLLCAL 600
601 GDGHLLNFQMDTTTGQLKDRKKVSLGTQPITLRTFSSKSATHVFAASDRP 650
651 TVIYSSNKKLLYSNVNLKEVSHMCPFNSAAFPDSLAIAREGELTIGTIDD 700
701 IQKLHIRTIPLGEHARRICHQEQTRTFGICSLGNQSNSEESEMHFVRLLD 750
751 DQTFEFMSTYPLDSFEYGCSILSCSFTEDKNVYYCVGTAYVLPEENEPTK 800
801 GRILVFIVEDGRLQLIAEKETKGAVYSLNAFNGKLLAAINQKIQLYKWML 850
851 RDDGTRELQSECGHHGHILALYVQTRGDFIVVGDLMKSISLLLYKHEEGA 900
901 IEERARDYNANWMSAVEILDDDIYLGAENNFNLLTVKKNSEGATDEERGR 950
951 LEVVGEYHLGEFVNRFRHGSLVMRLPDSEIGQIPTVIFGTVNGVIGVIAS 1000
1001 LPQEQYTFLEKLQSSLRKVIKGVGGLSHEQWRSFNNEKRTAEARNFLDGD 1050
1051 LIESFLDLSRNKMEDISKSMNVQVEELCKRVEELTRLH 1088
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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