 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9Y6M7 from www.uniprot.org...
The NucPred score for your sequence is 0.70 (see score help below)
1 MERFRLEKKLPGPDEEAVVDLGKTSSTVNTKFEKEELESHRAVYIGVHVP 50
51 FSKESRRRHRHRGHKHHHRRRKDKESDKEDGRESPSYDTPSQRVQFILGT 100
101 EDDDEEHIPHDLFTEMDELCYRDGEEYEWKETARWLKFEEDVEDGGDRWS 150
151 KPYVATLSLHSLFELRSCILNGTVMLDMRASTLDEIADMVLDNMIASGQL 200
201 DESIRENVREALLKRHHHQNEKRFTSRIPLVRSFADIGKKHSDPHLLERN 250
251 GEGLSASRHSLRTGLSASNLSLRGESPLSLLLGHLLPSSRAGTPAGSRCT 300
301 TPVPTPQNSPPSSPSISRLTSRSSQESQRQAPELLVSPASDDIPTVVIHP 350
351 PEEDLEAALKGEEQKNEENVDLTPGILASPQSAPGNLDNSKSGEIKGNGS 400
401 GGSRENSTVDFSKVDMNFMRKIPTGAEASNVLVGEVDFLERPIIAFVRLA 450
451 PAVLLTGLTEVPVPTRFLFLLLGPAGKAPQYHEIGRSIATLMTDEIFHDV 500
501 AYKAKDRNDLLSGIDEFLDQVTVLPPGEWDPSIRIEPPKSVPSQEKRKIP 550
551 VFHNGSTPTLGETPKEAAHHAGPELQRTGRLFGGLILDIKRKAPFFLSDF 600
601 KDALSLQCLASILFLYCACMSPVITFGGLLGEATEGRISAIESLFGASLT 650
651 GIAYSLFAGQPLTILGSTGPVLVFEKILYKFCRDYQLSYLSLRTSIGLWT 700
701 SFLCIVLVATDASSLVCYITRFTEEAFAALICIIFIYEALEKLFDLGETY 750
751 AFNMHNNLDKLTSYSCVCTEPPNPSNETLAQWKKDNITAHNISWRNLTVS 800
801 ECKKLRGVFLGSACGHHGPYIPDVLFWCVILFFTTFFLSSFLKQFKTKRY 850
851 FPTKVRSTISDFAVFLTIVIMVTIDYLVGVPSPKLHVPEKFEPTHPERGW 900
901 IISPLGDNPWWTLLIAAIPALLCTILIFMDQQITAVIINRKEHKLKKGAG 950
951 YHLDLLMVGVMLGVCSVMGLPWFVAATVLSISHVNSLKVESECSAPGEQP 1000
1001 KFLGIREQRVTGLMIFILMGLSVFMTSVLKFIPMPVLYGVFLYMGVSSLK 1050
1051 GIQLFDRIKLFGMPAKHQPDLIYLRYVPLWKVHIFTVIQLTCLVLLWVIK 1100
1101 VSAAAVVFPMMVLALVFVRKLMDLCFTKRELSWLDDLMPESKKKKEDDKK 1150
1151 KKEKEEAERMLQDDDDTVHLPFEGGSLLQIPVKALKYSPDKPVSVKISFE 1200
1201 DEPRKKYVDAETSL 1214
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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