 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q4VGL6 from www.uniprot.org...
The NucPred score for your sequence is 0.89 (see score help below)
1 MPVQAPQWTDFLSCPICTQTFDETIRKPISLGCGHTVCKMCLNKLHRKAC 50
51 PFDQTTINTDIELLPVNSALLQLVGAQIPEQQPITLCSGVEDTKHYEEAK 100
101 KCVEELALYLKPLSSARGVGLNSTTQSVLSRPMQRKLVTLVHCQLVEEEG 150
151 RIRAMRAARSLGERTVTELILQHQNPQQLSSNLWAAVRARGCQFLGPAMQ 200
201 EEALKLVLLALEDGSALSRKVLVLFVVQRLEPRFPQASKTSIGHVVQLLY 250
251 RASCFKVTKRDEDSSLMQLKEEFRTYEALRREHDSQIVQIAMEAGLRIAP 300
301 DQWSSLLYGDQSHKSHMQSIIDKLQTPASFAQSVQELTIALQRTGDPANL 350
351 NRLRPHLELLANIDPSPDAPPPTWEQLENGLVAVRTVVHGLVDYIQNHSK 400
401 KGADQQQPPQHSKYKTYMCRDMKQRGGCPRGASCTFAHSQEELEKFRKMN 450
451 KRLVPRRPLSASLGQLNEVGLPSAPILSDESAVDLSNRKPPALPNGIASS 500
501 GSTVTQLIPRGTDPSFDSSLKPVKLDHLSSSAPGSPPDLLESAPKSISAL 550
551 PVNPHPVPPRGPTDLPPMPVTKPIQMVPRGSQLYPAQQADVYYQDPRGSA 600
601 PAFETAPYQQGMYYTPPPCVSRFVRPPPSAPEPGPPYLDHYSPYLQDRVI 650
651 NSQYGTQPQQYPPMYPAHYDGRRVYPAQSYTREEMFRESPIPIDIPSAAV 700
701 PSYVPESRERYQQVEGYYPVAPHPAQIRPSYPRDPPYSRLPPPQPHPSLD 750
751 ELHRRRKEIMAQLEERKVISPPPFAPSPTLPPAFHPEEFLDEDLKVAGKY 800
801 KANDYSQYSPWSCDTIGSYIGTKDAKPKDVVAAGSVEMMNVESKGTREQR 850
851 LDLQRRAVETSDDDLIPFGDRPTVSRFGAISRTSKTLYQGAGPLQAIAPQ 900
901 GAPTKSINISDYSAYGAHGGWGDSPYSPHANIPPQGHFIEREKMSMAEVA 950
951 SHGKPLLSAEREQLRLELQQLNHQISQQTQLRGLEAVSNRLVLQREVNTL 1000
1001 ASQPQPPQLPPKWPGMISSEQLSLELHQVEREIGKRTRELSMENQCSVDM 1050
1051 KSKLGTSKQAENGQPEPQNKIRTEDLTLTFSDVPNGSALTQENLSLLSNK 1100
1101 TSSLNLSEDSEGGGDNNDSQRSGVVSNSAP 1130
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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