 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q61818 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MQSFRERCGFHGKQQNYPQTSQETSRLENYRQPGQAGLSCDRQRLLAKDY 50
51 YSPQPYTGYEGGTGTPSGTVATAAADKYHRGSKSLQGRPAFPSYVQDSSP 100
101 YPGRYSGEEGLQTWGGPQPPPPQPQPLPGAVSKYEENLMKKTVVPPPNRQ 150
151 YPEQGPQLPFRTHSLHVPPPQPQQPLAYPKLQRQKPQNDLASPLPFPQGS 200
201 HFPQHSQSFPTSSTYAPTVQGGGQGAHSYKSCTAPSAQPHDRPMSANANL 250
251 APGQRVQNLHAYQPGRLGYEQQQQALQGRHHTQETLHYQNLAKYQHYGQQ 300
301 GQGYCPPDTAVRTPEQYYQTFSPSSSHSPARSVGRSPSYSSTPSPLMPNL 350
351 ENFPYSQQPLSTGAFPTGITDHSHFMPLLNPSPTDAASSVDPQAGNCKPL 400
401 QKEKLPDNLLSDLSLQSLTALTSQVENISNTVQQLLLSKATMPQKKGVKN 450
451 LVSRTPEQHKSQHCSPEGSGYSAEPAGTPLSEPPSSTPQSTHAEPQDTDY 500
501 LSGSEDPLERSFLYCSQARGSPARVNSNSKAKPESVSTCSVTSPDDMSTK 550
551 SDDSFQSLHSTLPLDSFSKFVAGERDCPRLLLSALAQEDLASEILGLQEA 600
601 IVEKADKAWAEASSLPKDNGKPPFSLENHGACLDTVAKTSWSQPGEPETL 650
651 PEPLQLDKGGSTKDFSPGLFEDPSVAFATTDPKKTSSPLSFGTKPLLGTA 700
701 TPDPTTAAFDCFPDTPTASSVDGANPFAWPEENLGDACPRWGLHPGELTK 750
751 GLEQGAKASDGVGKADAHEASACMGFQEDHAIGKPAAALSGDFKQQEAEG 800
801 VKEEVGGLLQCPEVAKANQWLEESRHCCSSTDFGDLPLLPPPGRKEDLEA 850
851 EEEYSSLCELLGSPEQRPSLQDPLSPKAPLMCTKEEAEEALDTKAGWVSP 900
901 CHLSGEPAVLLGPSVGAQSKVQSWFESSLSHMKPGEEGPEMERAPGSSGT 950
951 SQGSLAPKPNKPAVPEGPIAKKEPVPRGKSLRSRRVHRGLPEAEDSPCRV 1000
1001 PALPKDLLLPESCTGPPQGQAEGAGAPGRGLSEGLPRMCTRSLTALSEPQ 1050
1051 TPGPPGLTTTPTPPDKLGGKQRAAFKSGKRVGKPSPKAASSPSNPAALPV 1100
1101 ASDSSPMGSKTKEPDSPSMPGKDQRSMVLRSRTKPQQVFHAKRRRPSESR 1150
1151 IPDCRATKKLPANNHLPTAYKVSSGPQKEGRMNQRVKVPKPGTGNKLSDR 1200
1201 PLHTLKRKSAFMAPVPAKKRSLILRSNNGSGGDGREERAESSPGLLRRMA 1250
1251 SPQRARPRGSGEPPPPPPLEPPAACMGLSTQSSLPSAVRTKVLPPRKGRG 1300
1301 LKLEAIVQKITSPGLKKLACRVAGAPPGTPRSPALPERRPGGSPAGAEEG 1350
1351 LGGMGQMLPAASGADPLCRNPASRSLKGKLLNSKKLSSAADCPKAEAFMS 1400
1401 PETLPSLGTARAPKKRSRKGRTGTLGPSKGPLEKRPCPGQPLLLAPHDRA 1450
1451 SSTQGGGEDNSSGGGKKPKTEELGPASQPPEGRPCQPQTRAQKQPGQASY 1500
1501 SSYSKRKRLSRGRGKTAHASPCKGRATRRRQQQVLPLDPAEPEIRLKYIS 1550
1551 SCKRLRADSRTPAFSPFVRVEKRDAYTTICTVVNSPGDEPKPHWKPSSSA 1600
1601 ASSSTSSSSLEPAGASLTTFPGGSVLQQRPSLPLSSTMHLGPVVSKALST 1650
1651 SCLVCCLCQNPANFKDLGDLCGPYYPEHCLPKKKPKLKEKARLEGTLEEA 1700
1701 SLPLERTLKGLECSASTTAAAPTTATITTPTALGRLSRPDGPADPAKQGP 1750
1751 LRTSARGLSRRLQSCYCCDGQGDGGEEVAQADKSRKHECSKEAPTEPGGD 1800
1801 TQEHWVHEACAVWTSGVYLVAGKLFGLQEAMKVAVDMPCTSCHEPGATIS 1850
1851 CSYKGCIHTYHYPCANDTGCTFIEENFTLKCPKHKRLPL 1889
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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