 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9CWL2 from www.uniprot.org...
The NucPred score for your sequence is 0.91 (see score help below)
1 MDLGTAESTRCTDPPAGKPPMAAKRKGGLKLNAICAKLSRQVVVEKGAEA 50
51 GSQAEGSPLHPRDKERSGPESGVSRAPRSEEDKRRAVIEKWVNGEYCEDP 100
101 APTPVLGRIARDQELPPEGVYMVQPQGCSDEEDHAEEPSKDNSVLEEKES 150
151 DGTASKDDSGPSTRQASGETSSLRDYAASTMTEFLGMFGYDDQNTRDELA 200
201 KKISFEKPHAGSTPEVAASSMLPSSEDTLSKRARFSKYEEYIRKLKAGEQ 250
251 LPWPAHGSKAEDRAGKEVVGPLPSLRLPSNTAHLETKATILPLPSHSSVQ 300
301 MQNLVARASKYDFFIHKLKTGENLRPQNGSTYKKPSKYDLENVKYLHLFK 350
351 PGEGSPDMGGAIAFKTGKVGRPSKYDVRGIQKPGPTKIPPAPSLVPTPLT 400
401 NVPSAPSTPGPGPEPPASLSFNTPEYLKSTFSKTDSITTGTVSTVKNGLP 450
451 TDKPAVTEDVNIYQKYIARFSGSQHCGHIHCAYQYREHYHCLDPECNYQR 500
501 FTSKQDVIRHYNMHKKRDNSLQHGFMRFSPLDDCSVYYHGCHLNGKSTHY 550
551 HCMQVGCNKVYTSTSDVMTHENFHKKNTQLINDGFQRFRATEDCGTADCQ 600
601 FYGQKTTHFHCRRPGCTFTFKNKCDIEKHKSYHIKDDAYAKDGFKKFYKY 650
651 EECKYEGCMYSKATNHFHCIRAGCGFTFTSTSQMTSHKRKHERRHIRSSG 700
701 ALGLPASLLGAKDTEHEESSNDDLVDFSALSSKNSSLSASPTSQQSSASL 750
751 AAAAAATTAEAIPSATKPPNSKMAGLLPQGLSGSIPLALALSNSGLPTTT 800
801 PYFPLLPNRGSASLPVGSPGLLGSMSSGATTSATPDMPALMASRAGDSAP 850
851 TAATSLSVPPASIIERISASKGLISPMMARLAAAALKPSATFDPGSGQQP 900
901 TPTKFPQAQVKQEPDSAGTPGPHEASQDRSLDLTVKDPSNESNGHAVSAN 950
951 SSLLSSLMNKMSQGNPSLESFLSIKTEAEGSPAGEPSPFLGKAVKALVQE 1000
1001 KLSEPWKVYLRRFGTKDFCDAQCDFLHKAHFHCVVEECGALFSTLDGAIK 1050
1051 HANFHFRTEGGTAKGTPEASFPTSAAETKPPLAPSSLPAPPGTMVAGSSL 1100
1101 EGPAPSPVSVPSTPTLLAWKQLASTIPQMPQIPSSVPHLPTSPLATTSLE 1150
1151 SAKPQVKPGFLQFQDNDPCLATDCKYASKFHFHCLFGNCKYVCKTSGKAE 1200
1201 SHCLDHINPSNSLVNVRDQFAYYSLQCLCPNQHCEFRMRGHYHCLRTGCY 1250
1251 FVTNITTKLPWHIKKHEKAERRAANGFKYFTKREECGRLGCKYNQVNSHF 1300
1301 HCIREGCQFSFLLKHQMTSHARKHMRRMLGKNFDRVPPSQGPPSLMDAET 1350
1351 DEGMDYTGCSPGAASSESSTMDRSCSSTPVGNESTAAGNTISMPTASGAK 1400
1401 KRFWIIEDMSPFGKRRKTASSRKMLDEGMMLEGFRRFDLYEDCKDTACQF 1450
1451 SLKVTHYHCTRENCGYKFCGRTHMYKHAQHHDRVDNLVLDDFKRFKASLS 1500
1501 CHFADCPFSGTSTHFHCLRCRFRCTDSTKVTAHRKHHGKQDVISAAGFCQ 1550
1551 FSSSADCAVPDCKYKLKCSHFHCTYPGCRHTVVGMSQMDSHKRKHEKQER 1600
1601 GEPPAASPGAPVNLDGSLTLAAEQGSLLFLQTAAAGLGLLGDTGDPGPPV 1650
1651 TASGTRDGPAAPTPAAAATTTTTTTATATATAGESSQEDDEELELPEEEA 1700
1701 EDDDEDDDEEDDDDEDDDDDDDDEDLRTDSEESLPEAAGEAGARTPLAAL 1750
1751 GGPGPAPTAAS 1761
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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