 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9W1X4 from www.uniprot.org...
The NucPred score for your sequence is 0.59 (see score help below)
1 MAQNAPDCEDTQDFQFKLHHKIVAFKKCGEPRSNVNLLAVSSSRGLLFAG 50
51 SPTQPELKVIIVKDLVNAKSTAQQPQARLVPLPSIPNYIACSSDGNLLAV 100
101 NHTQNGTSLLSIYAVLSFMTPDVRPVYNIRLAAEDHVHGVQLLWNPVLPN 150
151 SLAVVLSNGALAMYALKEGGNFEMHSLDKNQQVKCGCWSPKGKQIVLGFP 200
201 GGTVKQFKPDLTLAKTLLCPPNIHDAPFDTIAIQWLSTFQFAVIFLQHGE 250
251 DCSPSLYILNAPKAGAPSYINYYDICYSMNGPRNHQFVFSHVPQWNLLLV 300
301 VSANGVEVGIMRSTEAGDTPAWQQLTLLDEARIEMPLSEDKDETFPLGFA 350
351 FDTSTTHQLTINEKKLQTMPMVHVLSSDGELLSFNFLNVLPTAVSVCSPP 400
401 PPVADTSGQFKPLNMLLASEEEEQPAWAASPSKAPAATPAASSDISFAFT 450
451 PNTVTSTPAPSKDKQPSLFSGFGAAAAKAPAPQLSFGTAPTSSPVSFGAP 500
501 TTNAAKPTTPFGGFGTQATTTAMGSMFSASGANAFGGMALNKPAIASVTP 550
551 RTAAPGSTVPATPASAPANKPLYTVPLTFTPVDTKPATSAPPQIADESLK 600
601 PDDTEPIIKDMIALQIEAFSKDIQKQKEQTKELLKGIAAPSALRAYAKRL 650
651 DDLQELNEQAKDVEFELDVQGLRQGLNEAYAIVAECRGKLEIYRKPEITR 700
701 LMNSSSCDPSGRRMLARLQSYVAANEAQLRLAQQHVDLQWEQFQDVVRRN 750
751 SKSRMHMPCLEGIYQRLTRLQNLTSNQRIVQNNIKSKLKERGLLQAALLD 800
801 QEKSRTRTNEAVDTLTDSILTMSLSQVVDSNAAKLTRERLQKIRNIVQLQ 850
851 KINVICPQRPDRVGLKSEVILETKRRAEQIKRAAAKPATANKYTQAAVAP 900
901 PSPPDVAPTPAVAPMPQATVTVAPPLPKPMPSIPSVVEKPGVPTHPTTPV 950
951 ATPFSFSQSIPFVKTSTVTPTTNTVTPGEAAKPGLSIFGGSTISSFSFGG 1000
1001 GAAKSALSFGTGSPAVAAPTPKPNPLSAVEKPTPEPTKPKEQKAAESKEF 1050
1051 KAVQPETEESKVPQKPKAETENKSFGFGGFTGTGGTVGNTSSSPFSFGGL 1100
1101 GSSLGFGGTAAAVPKSEPSSTATTSVATSASTAPFGIFSAALAKPSNSEP 1150
1151 ITTVTSNTTTITSKPTNVIASSSVTDAPSVTTTNAVTSSTDPIGGLFSSV 1200
1201 TICKPNTPADTTKPANIFGGGLSAGSFSFGGTIDASKGLFGSTKPVATAP 1250
1251 TSVTEANNKTDPISTTPSAISTTTATTTVSSPAVVPAAVTAAVPATSSTT 1300
1301 VTSSTAVPGSAFSFSNAFSTLSAGGAAAPTTSASAPLAAKSPTATSTGNN 1350
1351 SSNSVFGGGFAVATSTAAPVASPFQSAAKSPVSSANIFGSIPKAETSVFG 1400
1401 GATTAPSNTTAAATPDAPPAGLFASAAISNPSPFGSPTTRAPASGGNIFG 1450
1451 QAVKPSVFGQPAQAGDSGGSIFGGGSASTPFGSSSIFGGGNTQGAVGAPA 1500
1501 AGSTSIFGQKVFGQSSAAAPAAGGNIFSNPVGSPQASPFGGGGNSIFGSP 1550
1551 ATAPPASGGSIFGGGSSSGGFGSFTQTTPAQGGFGGGFGQGGGGSVAQTG 1600
1601 FGSPQAPQQQTTTPGGFGAKPVFGGSPAFGASPTFGGGATFGSPKGFGGF 1650
1651 GGASPVASPPPFGAAAKPAQGNIFETLGGQESGLSFGNLAQTGNSNAQKP 1700
1701 AFGGSSFMNYR 1711
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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