 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q15811 from www.uniprot.org...
The NucPred score for your sequence is 0.95 (see score help below)
1 MAQFPTPFGGSLDIWAITVEERAKHDQQFHSLKPISGFITGDQARNFFFQ 50
51 SGLPQPVLAQIWALADMNNDGRMDQVEFSIAMKLIKLKLQGYQLPSALPP 100
101 VMKQQPVAISSAPAFGMGGIASMPPLTAVAPVPMGSIPVVGMSPTLVSSV 150
151 PTAAVPPLANGAPPVIQPLPAFAHPAATLPKSSSFSRSGPGSQLNTKLQK 200
201 AQSFDVASVPPVAEWAVPQSSRLKYRQLFNSHDKTMSGHLTGPQARTILM 250
251 QSSLPQAQLASIWNLSDIDQDGKLTAEEFILAMHLIDVAMSGQPLPPVLP 300
301 PEYIPPSFRRVRSGSGISVISSTSVDQRLPEEPVLEDEQQQLEKKLPVTF 350
351 EDKKRENFERGNLELEKRRQALLEQQRKEQERLAQLERAEQERKERERQE 400
401 QERKRQLELEKQLEKQRELERQREEERRKEIERREAAKRELERQRQLEWE 450
451 RNRRQELLNQRNKEQEDIVVLKAKKKTLEFELEALNDKKHQLEGKLQDIR 500
501 CRLTTQRQEIESTNKSRELRIAEITHLQQQLQESQQMLGRLIPEKQILND 550
551 QLKQVQQNSLHRDSLVTLKRALEAKELARQHLRDQLDEVEKETRSKLQEI 600
601 DIFNNQLKELREIHNKQQLQKQKSMEAERLKQKEQERKIIELEKQKEEAQ 650
651 RRAQERDKQWLEHVQQEDEHQRPRKLHEEEKLKREESVKKKDGEEKGKQE 700
701 AQDKLGRLFHQHQEPAKPAVQAPWSTAEKGPLTISAQENVKVVYYRALYP 750
751 FESRSHDEITIQPGDIVMVKGEWVDESQTGEPGWLGGELKGKTGWFPANY 800
801 AEKIPENEVPAPVKPVTDSTSAPAPKLALRETPAPLAVTSSEPSTTPNNW 850
851 ADFSSTWPTSTNEKPETDNWDAWAAQPSLTVPSAGQLRQRSAFTPATATG 900
901 SSPSPVLGQGEKVEGLQAQALYPWRAKKDNHLNFNKNDVITVLEQQDMWW 950
951 FGEVQGQKGWFPKSYVKLISGPIRKSTSMDSGSSESPASLKRVASPAAKP 1000
1001 VVSGEEFIAMYTYESSEQGDLTFQQGDVILVTKKDGDWWTGTVGDKAGVF 1050
1051 PSNYVRLKDSEGSGTAGKTGSLGKKPEIAQVIASYTATGPEQLTLAPGQL 1100
1101 ILIRKKNPGGWWEGELQARGKKRQIGWFPANYVKLLSPGTSKITPTEPPK 1150
1151 STALAAVCQVIGMYDYTAQNDDELAFNKGQIINVLNKEDPDWWKGEVNGQ 1200
1201 VGLFPSNYVKLTTDMDPSQQWCSDLHLLDMLTPTERKRQGYIHELIVTEE 1250
1251 NYVNDLQLVTEIFQKPLMESELLTEKEVAMIFVNWKELIMCNIKLLKALR 1300
1301 VRKKMSGEKMPVKMIGDILSAQLPHMQPYIRFCSRQLNGAALIQQKTDEA 1350
1351 PDFKEFVKRLAMDPRCKGMPLSSFILKPMQRVTRYPLIIKNILENTPENH 1400
1401 PDHSHLKHALEKAEELCSQVNEGVREKENSDRLEWIQAHVQCEGLSEQLV 1450
1451 FNSVTNCLGPRKFLHSGKLYKAKSNKELYGFLFNDFLLLTQITKPLGSSG 1500
1501 TDKVFSPKSNLQYKMYKTPIFLNEVLVKLPTDPSGDEPIFHISHIDRVYT 1550
1551 LRAESINERTAWVQKIKAASELYIETEKKKREKAYLVRSQRATGIGRLMV 1600
1601 NVVEGIELKPCRSHGKSNPYCEVTMGSQCHITKTIQDTLNPKWNSNCQFF 1650
1651 IRDLEQEVLCITVFERDQFSPDDFLGRTEIRVADIKKDQGSKGPVTKCLL 1700
1701 LHEVPTGEIVVRLDLQLFDEP 1721
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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