 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q90478 from www.uniprot.org...
The NucPred score for your sequence is 0.62 (see score help below)
1 EFRQRDPSPSFRWVKDGKQFGEVLSESGTLTPHPTMDLHFYQGTYRCYAA 50
51 NELGTAVSNLVHLTTEPVPSLAKVKKQKRRAYEVGESAVLRCNPPKSSVT 100
101 PKIHWMDMQFHHIPLNERVTISRDGNLYFANLIANDSRDDYTCNAHYINA 150
151 SIILPKEPMSIYVTPSNSVVKNRRAKLHHPAGARSSYLVLRGQTLTLQCI 200
201 PEGLPTPEVHWDRIDSALSPNRTKKLYNNRWLQIDNVLESDDGEYVCTAR 250
251 NSENSVKHHYTVTVEAAPYWTRSPEEHLYAPGETVRLDCKADGIPAPNIT 300
301 WSINGVPVSGTDVDPRRRVSSGKLILSNVEFSDTAVYQCEAVNKHGSILI 350
351 NTHVHVVELPAQILTPDERLYQATAGQTVMLDCRTFGSPLPKIHWEILDS 400
401 IPALSNAKISQTTNGSLKISNVSEEDSNRYTCSVSETNKSISADVEVLNR 450
451 TKIVGPPQNLHVIRGSDAILHCKYTVDHNLKSPTVQWNKDGHKITASTSN 500
501 DKYHEIEGSLKVLDVQMEDMGIYSCEVSTTLDSDTASGYITVQDKPDPPQ 550
551 SLKLSEKMERSVTISWMPSVENNSPVTEYVIEMNEGETPDEGQWQKYRSV 600
601 SQDIDSWRSICSYSKYHFQIRAVNSIGTSAPTESSLSYSTPAAKPDTNPE 650
651 NVMTLSTDPKSMIISWQEMDRRQFNGPGFQYKVFWRRAADSGAHWTESSV 700
701 SNPPLMVNNTGTFVSFEIKVQAVNDLGAAPEPLTVIGYSGEDFPLEAPSA 750
751 LSVTELQKTSVMVRWSPVRPESVRGHLLGYKIYLRMKGSQWETPGRAVSS 800
801 SGNPTVIEVPADAAEKIVSDLQFYSDYTLTITAFNSKGEGPHSEESFSTP 850
851 EGAPGPVLFLPFDSPSESEITLRWEAPHKPNGEIRGYLLQYQEVVIGSES 900
901 PQHVESIDLPAVTEFTLKNLNPESRYTFHLSARNDAGDGAPAIQSGATLL 950
951 DGEPPSVINMTAGETSVNLSWVPGDRHRNLGFSFRYLKKIEGAEWEESEK 1000
1001 INSTQAFYQLQGLDSGVIYHLQVLSGNTSYDWDFKTIYSPEWHKSPRNFA 1050
1051 TEGWFIGLISALVLLLLVLLLLCYIKKSKGGKYSVKDKEEGQGDAANQKL 1100
1101 KDDAFGEYRSLESDMEKCSISQPSGCESKRSSNDSLADYGDSVDIQFNED 1150
1151 GSFIGQYSGRRDPRGHDSSGAVSPVNPNMPPPSHSFPTSVTGILGPN 1197
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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