 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O13892 from www.uniprot.org...
The NucPred score for your sequence is 0.78 (see score help below)
1 MNEQDLLNSLRRDLNLPNLGKSHDGSEAVESTFPEKKESSLSAQQPHVDD 50
51 QRSSLLSLLNAGLNASNQSPSNSGPKYYASHSSSTDALLQAFRDGAKPSG 100
101 TASGADVKRSDSESTEATSNERPFNPVSAANLERLLMSSTGPQTPINGEL 150
151 KSNDSQDTAFQSSRNMPSDTSVASPDYSHSQSSSPIANYQESGNSEEPHK 200
201 AEEQQQLSIYQLDNPGSGNYVWETVISPDKFETSTFAKCERNDIAIINRE 250
251 LDAQDNQLIHTNEDFIAYAVHREPIIRVIEISTGKSFLLHNNSPNKFVSV 300
301 AWGNDSVIKNRLMAIDTTGQVLIFAVDIATSTSEIIFQLSGAQSLSDPIK 350
351 SRFHWYPKSSTRFAVALSKHIIFFDLDLLNNISFPIPRSINAIQQLPCFL 400
401 IDTGISAKEYDFSYDGTVFATVDKDALIKIYTVPTTFPSTPDKRPVPSEV 450
451 SPIAIFTTRMERGPSKNYEKPINLRFISTPGTNNSRYLVIVYVMNQLITL 500
501 FDLYSKRNIQTFRFNNRPTAATTTSFSQFSVDNERSTLLVGNPPSNSIYF 550
551 FLFAKDETVSEQAPIYNSTYELILASLNTSEPVPADAKFSVIVAKKFEKA 600
601 ACISFTACKILESEDKYCIVVSNTDGYEYYSIPTSILDKTGKTVRSLESV 650
651 QNYDADIGGTIDLTERHSTASPSTVNSGFSTPRSQATGFSKKKKDKGERF 700
701 ETKDKSSSVLSPSSYSASTFDAIPMDSIVSNILASLEKSVHKNYESLRSQ 750
751 LLEYKAANEKHTEAILSVVSSTLTENTGKILESVVEKSMQVALKEEIANS 800
801 VRNALKNNLEKIESFLENSIAELQNSVREDFDKQTSSLAQLRYSIQNVAH 850
851 AQKESEVKYNELNEQVKTLEGYVETVLEKFNDLKIENKVPETAPDVVPSS 900
901 YPPAAESNVSVSSDTSTKDVEKQEPSSAEQPAQGIAESLRRLKEYVKAGS 950
951 VKECVAEWCNMPSVAGFDVLSEISYDRMLENCSNLLLLTFIYHISLLDSV 1000
1001 DDDRLSKRMEYISRICLNIDVNDPKVETVVHPVLTLTREALLRQSEFFSP 1050
1051 IFKRRLVVLLRALDGKISEISVASSN 1076
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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