 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O42287 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MAQFGTPFGGNLDIWAITVEERAKHDQQFHGLKPTAGYITGDQARNFFLQ 50
51 SGLPQPVLAQIWALADMNNDGRMDQLEFSIAMKLIKLKLQGYPLPSILPS 100
101 NMLKQPVAMPAAAVAGFGMSGIVGIPPLAAVAPVPMPSIPVVGMSPPLVS 150
151 SVPTVPPLSNGAPAVIQSHPAFAHSATLPKSSSFGRSVAGSQINTKLQKA 200
201 QSFDVPAPPLVVEWAVPSSSRLKYRQLFNSQDKTMSGNLTGPQARTILMQ 250
251 SSLPQSQLATIWNLSDIDQDGKLTAEEFILAMHLIDVAMSGQPLPPILPP 300
301 EYIPPSFRRVRSGSGLSIMSSVSVDQRLPEEPEEEEPQNADKKLPVTFED 350
351 KKRENFERGNLELEKRRQALLEQQRKEQERLAQLERAEQERKERERQDQE 400
401 RKRQQDLEKQLEKQRELERQREEERRKEIERREAAKRELERQRQLEWERN 450
451 RRQELLNQRNREQEDIVVLKAKKKTLEFELEALNDKKHQLEGKLQDIRCR 500
501 LTTQRHEIESTNKSRELRIAEITHLQQQLQESQQLLGKMIPEKQSLNDQL 550
551 KQVQQNSLHRDSLLTLKRALETKEIGRQQLRDQLDEVEKETRAKLQEIDV 600
601 FNNQLKELRELYNKQQFQKQQDFETEKIKQKELERKTSELDKLKEEDKRR 650
651 MLEHDKLWQDRVKQEEERYKFQDEEKEKREESIQKCEVEKKPEIQEKPNK 700
701 PFHQPPEPGKLGGQIPWMNTEKAPLTINQGDVKVVYYRALYPFDARSHDE 750
751 ITIEPGDIIMVDESQTGEPGWLGGELKGKTGWFPANYAERMPESEFPSTT 800
801 KPAAETTAKPTVHVAPSPVAPAAFTNTSTNSNNWADFSSTWPTNNTDKVE 850
851 SDNWDTWAAQPSLTVPSAGQHRQRSAFTPATVTGSSPSPVLGQGEKVEGL 900
901 QAQALYPWRAKKDNHLNFNKNDVITVLEQQDMWWFGEVQGQKGWFPKSYV 950
951 KLISGPLRKSTSIDSTSSESPASLKRVSSPAFKPAIQGEEYISMYTYESN 1000
1001 EQGDLTFQQGDLIVVIKKDGDWWTGTVGEKTGVFPSNYVRPKDSEAAGSG 1050
1051 GKTGSLGKKPEIAQVIASYAATGPEQLTLAPGQLILIRKKNPGGWWEGEL 1100
1101 QARGKKRQIGWFPANYVKLLSPGTNKSTPTEPPKPTSLPPTCQVIGMYDY 1150
1151 IAQNDDELAFSKGQVINVLNKEDPDWWKGELNGHVGLFPSNYVKLTTDMD 1200
1201 PSQQWCADLHLLDMLSPTERKRQGYIHELIVTEENYVSDLQLVTETFQKP 1250
1251 LLESDLLTEKEVAMIFVNWKELIMCNIKLLKALRVRKKMSGEKMPVKMIG 1300
1301 DILTAQLPHMQPYIRFCSCQLNGAALIQQKTDEVPEFKEFVKRLAMDPRC 1350
1351 KGMPLSSFLLKPMQRVTRYPLIIKNIIENTPENHPDHSHLKQALEKAEEL 1400
1401 CSQVNEGVREKENSDRLEWIQGHVQCEGLSEQLVFNSVTNCLGPRKFLHS 1450
1451 GKLYKAKSNKELYGFLFNDFLLLTQIIKPLGSSGNDKVFSPKSNLQYKMY 1500
1501 KTPIFLNEVLVKLPTDPSGDEPIFHISHIDRVYTLRAESINERTAWVQKI 1550
1551 KAASELYIETEKKKREKAYLVRSQRATGIGRLMVNIVEGIELKPCRTHGK 1600
1601 SNPYCEITMGSQCHITKTIQDTLNPKWNSNCQFFIKDLEQDVLCITVFER 1650
1651 DQFSPDDFLGRTEIRVADIKKDQGSKGPVTKCLLLHEVPTGEIVVRLDLQ 1700
1701 LFDEP 1705
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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