 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q10407 from www.uniprot.org...
The NucPred score for your sequence is 0.82 (see score help below)
1 MAADIGSQSSGSLEERFEQSLHLQNVDKQDWSLNSVLQFLKLYKFNKEWE 50
51 DVFIKSRIEMDLFINLADQSKAEEFAFKNKLSKESAIQLSSCIRKTLLAP 100
101 SSTRVPSKNSSYETLTYSAKDSSDDVFTETNSGFRSSNQNSSLKSFQSVP 150
151 DSNVNVFGGFGGSVVDNNELLSTGKNSHQTTSLNLEGSPINLHAYKGTVT 200
201 SIINDDSRNINKKTLSKQPVSEHKEKQTSFLRRFRVPGFSRDKDKTKDCP 250
251 SSNSNPFHLASSNVKTLDASLDQGEWVPRIHRLESQIGLISKKKSFVLAT 300
301 MDDMKFTVVDITNVQNATQLRKLIAKSMYLDISIDQFDLFLTEVGGAQYI 350
351 EILDDRKLDIARLYSDEFGTIKFFVKPSQNEESGMDSDTYLSFGTKSSST 400
401 YKADDDSIYHRKEDFKKQPSYPVLTSDFEITDAGPNLSLSGHQPDNKYYK 450
451 GFSSAPNLAVVPELPSRRFRGFEKIRGAKGEMATKILDATEAQSEKNKFT 500
501 VCRPHKKVTLKMPLNSGSSAPQSPSSNTSASVLTRNFVAHRDPPPPPTET 550
551 SSLRRKNTLTRRPSIRHARSSPYIDTGHNEASKFSHTSFDPKASSKSSNS 600
601 LKESVEALSEIPFEDAPALDESDLSGDPFWAIQPKQSSSQVPKENHHNIQ 650
651 SKLSINTEAATDLKANELSSPKTPEYCRGDDRSISLSPLSYRLRKSKHIR 700
701 ESPPSSKVINSGNWEVRPSADDLYEDVDRFFPRYDLDKVLVVDQSRMVSS 750
751 PSKVSIRPKMKSVRLLAREASEARKEIRHNARRNKSGNLLRRSSTKLWGS 800
801 RIVELKPDTTITSGSVVSQNATFKWMKGELIGNGTYGKVFLAMNINTGEL 850
851 IAVKQVEIPQTINGRHDQLRKDIVDSINAEISMIADLDHLNIVQYLGFEK 900
901 TETDISIFLEYVSGGSIGRCLRNYGPFEEQLVRFVSRQVLYGLSYLHSKG 950
951 IIHRDLKADNLLIDFDGVCKISDFGISKHSDNVYDNDANLSMQGSIFWMA 1000
1001 PEVIHNDHQGYSAKVDVWSLGCVVLEMLAGRRPWSTDEAIQAMFKLGTEK 1050
1051 KAPPIPSELVSQVSPEAIQFLNACFTVNADVRPTAEELLNHPFMKCDEEF 1100
1101 NFKDTNLYDMLCKRKS 1116
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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