 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P16884 from www.uniprot.org...
The NucPred score for your sequence is 0.54 (see score help below)
1 MMSFGSADALLGAPFAPLHGGGSLHYALSRKAGAGGTRSAAGSSSGFHSW 50
51 ARTSVSSVSASPSRFRGAASSTDSLDTLSNGPEGCVAAVAARSEKEQLQA 100
101 LNDRFAGYIDKVRQLEAHNRTLEGEAAALRQQKGRAAMGELYEREVREMR 150
151 GAVLRLGAARGHVRLEQEHLLEDIAHVRQRLDEEARQREEAEAAARALAR 200
201 FAQEAEAARVELQKKAQALQEECGYLRRHHQEEVGELLGQIQGCGAAQAQ 250
251 AQAEARDALKCDVTSALREIRAQLEGHTVQSTLQSEEWFRVRLDRLSEAA 300
301 KVNTDAMRSAQEEITEYRRQLQARTTELEALKSTKESLERQRSELEDRHQ 350
351 VDMASYQDAIQQLDNELRNTKWEMAAQLREYQDLLNVKMALDIEIAAYRK 400
401 LLEGEECRIGFGPSPFSLTEGLPKIPSMSTHIKVKSEEKIKVVEKSEKET 450
451 VIVEEQTEEIQVTEEVTEEEDKEAQGEEEEEAEEGGEEAATTSPPAEEAA 500
501 SPEKETKSPVKEEAKSPAEAKSPAEAKSPAEAKSPAEVKSPAEVKSPAEA 550
551 KSPAEAKSPAEVKSPAEVKSPAEAKSPAEAKSPAEVKSPATVKSPGEAKS 600
601 PAEAKSPAEVKSPVEAKSPAEAKSPASVKSPGEAKSPAEAKSPAEVKSPA 650
651 TVKSPVEAKSPAEVKSPVTVKSPAEAKSPVEVKSPASVKSPSEAKSPAGA 700
701 KSPAEAKSPVVAKSPAEAKSPAEAKPPAEAKSPAEAKSPAEAKSPAEAKS 750
751 PAEAKSPVEVKSPEKAKSPVKEGAKSLAEAKSPEKAKSPVKEEIKPPAEV 800
801 KSPEKAKSPMKEEAKSPEKAKTLDVKSPEAKTPAKEEAKRPADIRSPEQV 850
851 KSPAKEEAKSPEKEETRTEKVAPKKEEVKSPVEEVKAKEPPKKVEEEKTP 900
901 ATPKTEVKESKKDEAPKEAQKPKAEEKEPLTEKPKDSPGEAKKEEAKEKK 950
951 AAAPEEETPAKLGVKEEAKPKEKAEDAKAKEPSKPSEKEKPKKEEVPAAP 1000
1001 EKKDTKEEKTTESKKPEEKPKMEAKAKEEDKGLPQEPSKPKTEKAEKSSS 1050
1051 TDQKDSQPSEKAPEDKAAKGDK 1072
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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