 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P53751 from www.uniprot.org...
The NucPred score for your sequence is 0.54 (see score help below)
1 MLMTGSVGDGSEFDWEDQKTFISRDGGLTWRFVHNSSGLYATGDLGNIIV 50
51 YIPYDPEEDGDFQSEFYYSLDQGRTWNEYELTNAISSVHPYKLINPTPDG 100
101 SGSKFIFKGTFATTDSETNSITSLKGVEYIIDFSAAFDSRTCEEEDFEDW 150
151 DLADGKCVNGAKYKYRRRKQDAQCLVKKAFKDLSLDETPCNSCGESDYEC 200
201 SFEFVRDANGLCIPDYNLIAFSNICDKSKDKSVLVEPLQLIKGDECKTPM 250
251 KIEPVDIPCDEIPEEGSSDREIVTTENKFDFEIKFYQYFDTVADESLVML 300
301 NSIGDAYISHDGGQTIKRFDTNGEKIVEVVFNPYFNSSAYLFGSKGNIFS 350
351 THDRGHSFMIAKLPEARQLGMPLDFSAKAQDTFIYYGGKNCESILSPECH 400
401 AVAYLTKDGGETFTEMLDNAIHCEFAGTLFEYPSNEEMVMCQVKKKSSET 450
451 RSLVSSIDFFQGDNKIIFENIIGYLSTGGYIIVAVPHEDNELRAYVTIDG 500
501 TEFAEAKFPYGQDVSKQEAFTILGSEKGSIFLHLATNLESGHDFGNLLKS 550
551 NSNGTSFVTLEHAVNRNTFGYVDFEKVQGLEGIIITNIVSNREKVGENKE 600
601 DEQLKTKITFNDGSDWNFLKPPKKDSEGKKFPCDSVSLDKCSLHLHGYTE 650
651 RKDIRDTYSSGSALGMMFGVGNVGDKLLPYEECSTFLTTDGGETWTEVKK 700
701 GPHQWEYGDHGGVLVLVPENAETDSISYSTDFGKTWKDYKFCGDKVLVKD 750
751 IITVPRDSALRFLLFGEAKNMGSGSFRTYTIDFRNIFERQCEFDITGKKR 800
801 ADFKYSPLGSRTGCLFGHQTEFLRKTDEKCFIGNIPLSEFSRNVKNCSCT 850
851 RQDFECDYNFYKASDGTCKLVKGLSSANGADICKKEPDLIEYYDSSGYRK 900
901 IPLSTCKGGLKLDAHLAPHPCPGKEKAFREKYSINTGAYALVFVTILLVI 950
951 FFAAWFVYDRGIRRNGGFSRFEEIRLGDDGLIENNRTDRVVNIIVRLGLC 1000
1001 ISLITKSAFQRTKAGVARFSSKLRARFGNRKGPTYSSLLQGQFSDESDGL 1050
1051 HEDANDLSSFTSQDSNFEIEQEDAYRPEQEHTSQIDQPATSNIPDALPAR 1100
1101 SAIHKPDSTAVRNEDE 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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