 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9HBD1 from www.uniprot.org...
The NucPred score for your sequence is 0.86 (see score help below)
1 MPVQAAQWTEFLSCPICYNEFDENVHKPISLGCSHTVCKTCLNKLHRKAC 50
51 PFDQTAINTDIDVLPVNFALLQLVGAQVPDHQSIKLSNLGENKHYEVAKK 100
101 CVEDLALYLKPLSGGKGVASLNQSALSRPMQRKLVTLVNCQLVEEEGRVR 150
151 AMRAARSLGERTVTELILQHQNPQQLSANLWAAVRARGCQFLGPAMQEEA 200
201 LKLVLLALEDGSALSRKVLVLFVVQRLEPRFPQASKTSIGHVVQLLYRAS 250
251 CFKVTKRDEDSSLMQLKEEFRSYEALRREHDAQIVHIAMEAGLRISPEQW 300
301 SSLLYGDLAHKSHMQSIIDKLQSPESFAKSVQELTIVLQRTGDPANLNRL 350
351 RPHLELLANIDPNPDAVSPTWEQLENAMVAVKTVVHGLVDFIQNYSRKGH 400
401 ETPQPQPNSKYKTSMCRDLRQQGGCPRGTNCTFAHSQEELEKYRLRNKKI 450
451 NATVRTFPLLNKVGVNNTVTTTAGNVISVIGSTETTGKIVPSTNGISNAE 500
501 NSVSQLISRSTDSTLRALETVKKVGKVGANGQNAAGPSADSVTENKIGSP 550
551 PKTPVSNVAATSAGPSNVGTELNSVPQKSSPFLTRVPVYPPHSENIQYFQ 600
601 DPRTQIPFEVPQYPQTGYYPPPPTVPAGVAPCVPRFVRSNNVPESSLPPA 650
651 SMPYADHYSTFSPRDRMNSSPYQPPPPQPYGPVPPVPSGMYAPVYDSRRI 700
701 WRPPMYQRDDIIRSNSLPPMDVMHSSVYQTSLRERYNSLDGYYSVACQPP 750
751 SEPRTTVPLPREPCGHLKTSCEEQIRRKPDQWAQYHTQKAPLVSSTLPVA 800
801 TQSPTPPSPLFSVDFRADFSESVSGTKFEEDHLSHYSPWSCGTIGSCINA 850
851 IDSEPKDVIANSNAVLMDLDSGDVKRRVHLFETQRRTKEEDPIIPFSDGP 900
901 IISKWGAISRSSRTGYHTTDPVQATASQGSATKPISVSDYVPYVNAVDSR 950
951 WSSYGNEATSSAHYVERDRFIVTDLSGHRKHSSTGDLLSLELQQAKSNSL 1000
1001 LLQREANALAMQQKWNSLDEGRHLTLNLLSKEIELRNGELQSDYTEDATD 1050
1051 TKPDRDIELELSALDTDEPDGQSEPIEEILDIQLGISSQNDQLLNGMAVE 1100
1101 NGHPVQQHQKEPPKQKKQSLGEDHVILEEQKTILPVTSCFSQPLPVSISN 1150
1151 ASCLPITTSVSAGNLILKTHVMSEDKNDFLKPVANGKMVNS 1191
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.) |
Go back to the NucPred Home Page.