 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9UDY2 from www.uniprot.org...
The NucPred score for your sequence is 0.67 (see score help below)
1 MPVRGDRGFPPRRELSGWLRAPGMEELIWEQYTVTLQKDSKRGFGIAVSG 50
51 GRDNPHFENGETSIVISDVLPGGPADGLLQENDRVVMVNGTPMEDVLHSF 100
101 AVQQLRKSGKVAAIVVKRPRKVQVAALQASPPLDQDDRAFEVMDEFDGRS 150
151 FRSGYSERSRLNSHGGRSRSWEDSPERGRPHERARSRERDLSRDRSRGRS 200
201 LERGLDQDHARTRDRSRGRSLERGLDHDFGPSRDRDRDRSRGRSIDQDYE 250
251 RAYHRAYDPDYERAYSPEYRRGARHDARSRGPRSRSREHPHSRSPSPEPR 300
301 GRPGPIGVLLMKSRANEEYGLRLGSQIFVKEMTRTGLATKDGNLHEGDII 350
351 LKINGTVTENMSLTDARKLIEKSRGKLQLVVLRDSQQTLINIPSLNDSDS 400
401 EIEDISEIESNRSFSPEERRHQYSDYDYHSSSEKLKERPSSREDTPSRLS 450
451 RMGATPTPFKSTGDIAGTVVPETNKEPRYQEDPPAPQPKAAPRTFLRPSP 500
501 EDEAIYGPNTKMVRFKKGDSVGLRLAGGNDVGIFVAGIQEGTSAEQEGLQ 550
551 EGDQILKVNTQDFRGLVREDAVLYLLEIPKGEMVTILAQSRADVYRDILA 600
601 CGRGDSFFIRSHFECEKETPQSLAFTRGEVFRVVDTLYDGKLGNWLAVRI 650
651 GNELEKGLIPNKSRAEQMASVQNAQRDNAGDRADFWRMRGQRSGVKKNLR 700
701 KSREDLTAVVSVSTKFPAYERVLLREAGFKRPVVLFGPIADIAMEKLANE 750
751 LPDWFQTAKTEPKDAGSEKSTGVVRLNTVRQIIEQDKHALLDVTPKAVDL 800
801 LNYTQWFPIVIFFNPDSRQGVKTMRQRLNPTSNKSSRKLFDQANKLKKTC 850
851 AHLFTATINLNSANDSWFGSLKDTIQHQQGEAVWVSEGKMEGMDDDPEDR 900
901 MSYLTAMGADYLSCDSRLISDFEDTDGEGGAYTDNELDEPAEEPLVSSIT 950
951 RSSEPVQHEESIRKPSPEPRAQMRRAASSDQLRDNSPPPAFKPEPPKAKT 1000
1001 QNKEESYDFSKSYEYKSNPSAVAGNETPGASTKGYPPPVAAKPTFGRSIL 1050
1051 KPSTPIPPQEGEEVGESSEEQDNAPKSVLGKVKIFEKMDHKARLQRMQEL 1100
1101 QEAQNARIEIAQKHPDIYAVPIKTHKPDPGTPQHTSSRPPEPQKAPSRPY 1150
1151 QDTRGSYGSDAEEEEYRQQLSEHSKRGYYGQSARYRDTEL 1190
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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