 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q5B1X8 from www.uniprot.org...
The NucPred score for your sequence is 0.30 (see score help below)
1 MATTSHMFMYSLTIQPPTAITQAILGQFAGTKEQQIVTASGSKLTIHRPD 50
51 PTQGKVIPLYTQDVFGIIRTLAAFRLAGSNKDYIIIGSDSGRITIIEYVP 100
101 SQNRFNRIHLETFGKSGVRRVVPGQYLAVDPKGRACLIASVEKNKLVYVL 150
151 NRNSQAELTISSPLEAHKPQTLVYSVVALDAGYENPVFAALEVDYSESDQ 200
201 DPTGRAYEEVEKLLVYYELDLGLNHVVRKWTDPVDRTSSMLFQVPGGADG 250
251 PSGVLVCAEDNITYRHSNQDAFRVPIPRRKGAMENPERKRCITAGVMHKM 300
301 RGAFFFLLQTEDGDLFKLTLDMVEDDKGQLTGEVKGLKIKYFDTVPLASS 350
351 LLILKSGFLYVAAEGGNHHFYQFEKLGDDDEETEFNSDDFSADPAAPCTP 400
401 VYFQPRGAENLNLVEAINSLNPLVDSKVVNISEDDAPQIFTVSGTGARST 450
451 FRTLKHGLEVSEIVESELPSVPSAVWTTKLTRADEFDAYIVLSFANGTLV 500
501 LSIGETVEEVTDTGFLSSAPTLAVQQLGEDSLIQIHPRGIRHILADRRVN 550
551 EWPAPQHRSIVAAATNERQVAVALSSGEIVYFELDADGSLAEYDERRQMS 600
601 GTVTCLSLGEVPEGRVRSSFLAVGCDDSTVRILSLDPDTTLENKSVQALT 650
651 AAPSALNIIAMADSSSGGTTLYLHIGLHSGVYLRTALDEVTGELSDTRTR 700
701 FLGSKAVKLFQVSVTGQTAVLALSSRPWLGYSDTQTKGFMLTPLDYVGLE 750
751 WGWNFSSEQCVEGMVGIQGQNLRIFSIEKLDNNMLQQSIPLAYTPRHFIK 800
801 HPEEPLFYVIEADNNVLSPATRARLLEDSKARGGDTTVLPPEDFGYPRGT 850
851 GHWASCIQIIDPLDAKAVVGAVELEENEAAVSIAAVPFTSQDDETFLVVG 900
901 TAKDMTVNPPSSAGGYIHIYRFQEDGKELEFIHKTKVEEPPLALLGFQGR 950
951 LLAGVGSVLRIYDLGMKQLLRKCQAAVAPKAIVGLQTQGSRIVVSDVRES 1000
1001 VTYVVYKYQDNVLIPFVDDSIARWTTAATMVDYETTAGGDKFGNLWLVRC 1050
1051 PKKASEEADEEGSGAHLIHDRGYLQGTPNRLELMIHVFTQDIPTSLHKTQ 1100
1101 LVAGGRDILVWTGFQGTIGILVPFVSREDVDFFQSLEMQLASQCPPLAGR 1150
1151 DHLIYRSYYAPVKGVIDGDLCEQYFLLSNDTKMMIAAELDRSVREIERKI 1200
1201 SDMRTRVAY 1209
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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