 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6QNU4 from www.uniprot.org...
The NucPred score for your sequence is 0.08 (see score help below)
1 MSVWNYVVTAHKPTNVTHSCVGNFTGPQELNLIIAKCTRIEIHLLTPQGL 50
51 QPMLDVPIYGRIATLELFRPHGETQDLLFIATERYKFCVLQWDTEASEVI 100
101 TRAMGDVSDRIGRPTDNGQIGIIDPDCRLIGLHLYDGLFKVIPFDNKGQL 150
151 KEAFNIRLEELQVLDIKFLYGCPKPTIVVLYQDNKDARHVKTYEVSLKDK 200
201 DFIEGPWAQNNLDNGASLLIPVPPPLCGVLIIGEETIVYCSASAFKAIPI 250
251 RPSITRAYGRVDADGSRYLLGDHNGLLHLLVITHEKEKVTGLKIELLGET 300
301 SIASTISYLDNAFVFIGSSYGDSQLVKLNLQPDTKGSYVEVLERYVNLGP 350
351 IVDFCVVDLERQGQGQVVTCSGAYKDGSLRIVRNGIGINEQASVELQGIK 400
401 GMWSLRSATDDPYDTFLVVSFISETRVLAMNLEDELEETEIEGFNSQVQT 450
451 LFCHDAVYNQLVQVTSNSVRLVSSTSRDLKNEWFAPVGYSVNVATANATQ 500
501 VLLATGGGHLVYLEIGDGVLNEVKYAKLDYDISCLDINPIGENPNYSNIA 550
551 AVGMWTDISVRIYSLPDLNLITKEQLGGEIIPRSVLMCSFEGISYLLCAL 600
601 GDGHLLNFVLSMSTGELTDRKKVSLGTQPITLRTFSSKDTTHVFAASDRP 650
651 TVIYSSNKKLLYSNVNLKEVSHMCPFNVAAFPDSLAIAKEGELTIGTIDE 700
701 IQKLHIRSIPLGEHARRISHQEQTRTFALCSVKYTQSNADDPEMHFVRLL 750
751 DDQTFEFISTYPLDQFEYGCSILSCSFSDDSNVYYCIGTAYVMPEENEPT 800
801 KGRILVFIVEDGKLQLIAEKETKGAVYSLNAFNGKLLAAINQKIQLYKWA 850
851 SREDGGSRELQTECGHHGHILALYVQTRGDFIVVGDLMKSISLLIFKHEE 900
901 GAIEERARDYNANWMSAVEILDDDIYLGAENNFNLFTVRKNSEGATDEER 950
951 SRLEVVGEYHLGEFVNRFRHGSLVMRLPDSDVGQIPTVIFGTVNGVIGVI 1000
1001 ASLPHDQYLFLEKLQTNLRKVIKGVGGLSHEQWRSFYNEKKTVDAKNFLD 1050
1051 GDLIESFLDLSRNRMEEISKAMSVPVEELMKRVEELTRLH 1090
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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