 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q91V92 from www.uniprot.org...
The NucPred score for your sequence is 0.08 (see score help below)
1 MSAKAISEQTGKELLYKYICTTSAIQNRFKYARVTPDTDWAHLLQDHPWL 50
51 LSQSLVVKPDQLIKRRGKLGLVGVNLSLDGVKSWLKPRLGHEATVGKAKG 100
101 FLKNFLIEPFVPHSQAEEFYVCIYATREGDYVLFHHEGGVDVGDVDAKAQ 150
151 KLLVGVDEKLNTEDIKRHLLVHAPEDKKEVLASFISGLFNFYEDLYFTYL 200
201 EINPLVVTKDGVYILDLAAKVDATADYICKVKWGDIEFPPPFGREAYPEE 250
251 AYIADLDAKSGASLKLTLLNPKGRIWTMVAGGGASVVYSDTICDLGGVNE 300
301 LANYGEYSGAPSEQQTYDYAKTILSLMTREKHPEGKILIIGGSIANFTNV 350
351 AATFKGIVRAIRDYQGPLKEHEVTIFVRRGGPNYQEGLRVMGEVGKTTGI 400
401 PIHVFGTETHMTAIVGMALGHRPIPNQPPTAAHTANFLLNASGSTSTPAP 450
451 SRTASFSESRADEVAPAKKAKPAMPQGKSATLFSRHTKAIVWGMQTRAVQ 500
501 GMLDFDYVCSRDEPSVAAMVYPFTGDHKQKFYWGHKEILIPVFKNMADAM 550
551 KKHPEVDVLINFASLRSAYDSTMETMNYAQIRTIAIIAEGIPEALTRKLI 600
601 KKADQKGVTIIGPATVGGIKPGCFKIGNTGGMLDNILASKLYRPGSVAYV 650
651 SRSGGMSNELNNIISRTTDGVYEGVAIGGDRYPGSTFMDHVLRYQDTPGV 700
701 KMIVVLGEIGGTEEYKICRGIKEGRLTKPVVCWCIGTCATMFSSEVQFGH 750
751 AGACANQASETAVAKNQALKEAGVFVPRSFDELGEIIQSVYEDLVAKGAI 800
801 VPAQEVPPPTVPMDYSWARELGLIRKPASFMTSICDERGQELIYAGMPIT 850
851 EVFKEEMGIGGVLGLLWFQRRLPKYSCQFIEMCLMVTADHGPAVSGAHNT 900
901 IICARAGKDLVSSLTSGLLTIGDRFGGALDAAAKMFSKAFDSGIIPMEFV 950
951 NKMKKEGKLIMGIGHRVKSINNPDMRVQILKDFVKQHFPATPLLDYALEV 1000
1001 EKITTSKKPNLILNVDGFIGVAFVDMLRNCGSFTREEADEYVDIGALNGI 1050
1051 FVLGRSMGFIGHYLDQKRLKQGLYRHPWDDISYVLPEHMSM 1091
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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