 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q13753 from www.uniprot.org...
The NucPred score for your sequence is 0.62 (see score help below)
1 MPALWLGCCLCFSLLLPAARATSRREVCDCNGKSRQCIFDRELHRQTGNG 50
51 FRCLNCNDNTDGIHCEKCKNGFYRHRERDRCLPCNCNSKGSLSARCDNSG 100
101 RCSCKPGVTGARCDRCLPGFHMLTDAGCTQDQRLLDSKCDCDPAGIAGPC 150
151 DAGRCVCKPAVTGERCDRCRSGYYNLDGGNPEGCTQCFCYGHSASCRSSA 200
201 EYSVHKITSTFHQDVDGWKAVQRNGSPAKLQWSQRHQDVFSSAQRLDPVY 250
251 FVAPAKFLGNQQVSYGQSLSFDYRVDRGGRHPSAHDVILEGAGLRITAPL 300
301 MPLGKTLPCGLTKTYTFRLNEHPSNNWSPQLSYFEYRRLLRNLTALRIRA 350
351 TYGEYSTGYIDNVTLISARPVSGAPAPWVEQCICPVGYKGQFCQDCASGY 400
401 KRDSARLGPFGTCIPCNCQGGGACDPDTGDCYSGDENPDIECADCPIGFY 450
451 NDPHDPRSCKPCPCHNGFSCSVMPETEEVVCNNCPPGVTGARCELCADGY 500
501 FGDPFGEHGPVRPCQPCQCNNNVDPSASGNCDRLTGRCLKCIHNTAGIYC 550
551 DQCKAGYFGDPLAPNPADKCRACNCNPMGSEPVGCRSDGTCVCKPGFGGP 600
601 NCEHGAFSCPACYNQVKIQMDQFMQQLQRMEALISKAQGGDGVVPDTELE 650
651 GRMQQAEQALQDILRDAQISEGASRSLGLQLAKVRSQENSYQSRLDDLKM 700
701 TVERVRALGSQYQNRVRDTHRLITQMQLSLAESEASLGNTNIPASDHYVG 750
751 PNGFKSLAQEATRLAESHVESASNMEQLTRETEDYSKQALSLVRKALHEG 800
801 VGSGSGSPDGAVVQGLVEKLEKTKSLAQQLTREATQAEIEADRSYQHSLR 850
851 LLDSVSRLQGVSDQSFQVEEAKRIKQKADSLSSLVTRHMDEFKRTQKNLG 900
901 NWKEEAQQLLQNGKSGREKSDQLLSRANLAKSRAQEALSMGNATFYEVES 950
951 ILKNLREFDLQVDNRKAEAEEAMKRLSYISQKVSDASDKTQQAERALGSA 1000
1001 AADAQRAKNGAGEALEISSEIEQEIGSLNLEANVTADGALAMEKGLASLK 1050
1051 SEMREVEGELERKELEFDTNMDAVQMVITEAQKVDTRAKNAGVTIQDTLN 1100
1101 TLDGLLHLMDQPLSVDEEGLVLLEQKLSRAKTQINSQLRPMMSELEERAR 1150
1151 QQRGHLHLLETSIDGILADVKNLENIRDNLPPGCYNTQALEQQ 1193
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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