 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P18616 from www.uniprot.org...
The NucPred score for your sequence is 0.81 (see score help below)
1 MDTRFPFSPAEVSKVRVVQFGILSPDEIRQMSVIHVEHSETTEKGKPKVG 50
51 GLSDTRLGTIDRKVKCETCMANMAECPGHFGYLELAKPMYHVGFMKTVLS 100
101 IMRCVCFNCSKILADEEEHKFKQAMKIKNPKNRLKKILDACKNKTKCDGG 150
151 DDIDDVQSHSTDEPVKKSRGGCGAQQPKLTIEGMKMIAEYKIQRKKNDEP 200
201 DQLPEPAERKQTLGADRVLSVLKRISDADCQLLGFNPKFARPDWMILEVL 250
251 PIPPPPVRPSVMMDATSRSEDDLTHQLAMIIRHNENLKRQEKNGAPAHII 300
301 SEFTQLLQFHIATYFDNELPGQPRATQKSGRPIKSICSRLKAKEGRIRGN 350
351 LMGKRVDFSARTVITPDPTINIDELGVPWSIALNLTYPETVTPYNIERLK 400
401 ELVDYGPHPPPGKTGAKYIIRDDGQRLDLRYLKKSSDQHLELGYKVERHL 450
451 QDGDFVLFNRQPSLHKMSIMGHRIRIMPYSTFRLNLSVTSPYNADFDGDE 500
501 MNMHVPQSFETRAEVLELMMVPKCIVSPQANRPVMGIVQDTLLGCRKITK 550
551 RDTFIEKDVFMNTLMWWEDFDGKVPAPAILKPRPLWTGKQVFNLIIPKQI 600
601 NLLRYSAWHADTETGFITPGDTQVRIERGELLAGTLCKKTLGTSNGSLVH 650
651 VIWEEVGPDAARKFLGHTQWLVNYWLLQNGFTIGIGDTIADSSTMEKINE 700
701 TISNAKTAVKDLIRQFQGKELDPEPGRTMRDTFENRVNQVLNKARDDAGS 750
751 SAQKSLAETNNLKAMVTAGSKGSFINISQMTACVGQQNVEGKRIPFGFDG 800
801 RTLPHFTKDDYGPESRGFVENSYLRGLTPQEFFFHAMGGREGLIDTAVKT 850
851 SETGYIQRRLVKAMEDIMVKYDGTVRNSLGDVIQFLYGEDGMDAVWIESQ 900
901 KLDSLKMKKSEFDRTFKYEIDDENWNPTYLSDEHLEDLKGIRELRDVFDA 950
951 EYSKLETDRFQLGTEIATNGDSTWPLPVNIKRHIWNAQKTFKIDLRKISD 1000
1001 MHPVEIVDAVDKLQERLLVVPGDDALSVEAQKNATLFFNILLRSTLASKR 1050
1051 VLEEYKLSREAFEWVIGEIESRFLQSLVAPGEMIGCVAAQSIGEPATQMT 1100
1101 LNTFHYAGVSAKNVTLGVPRLREIINVAKRIKTPSLSVYLTPEASKSKEG 1150
1151 AKTVQCALEYTTLRSVTQATEVWYDPDPMSTIIEEDFEFVRSYYEMPDED 1200
1201 VSPDKISPWLLRIELNREMMVDKKLSMADIAEKINLEFDDDLTCIFNDDN 1250
1251 AQKLILRIRIMNDEGPKGELQDESAEDDVFLKKIESNMLTEMALRGIPDI 1300
1301 NKVFIKQVRKSRFDEEGGFKTSEEWMLDTEGVNLLAVMCHEDVDPKRTTS 1350
1351 NHLIEIIEVLGIEAVRRALLDELRVVISFDGSYVNYRHLAILCDTMTYRG 1400
1401 HLMAITRHGINRNDTGPLMRCSFEETVDILLDAAAYAETDCLRGVTENIM 1450
1451 LGQLAPIGTGDCELYLNDEMLKNAIELQLPSYMDGLEFGMTPARSPVSGT 1500
1501 PYHEGMMSPNYLLSPNMRLSPMSDAQFSPYVGGMAFSPSSSPGYSPSSPG 1550
1551 YSPTSPGYSPTSPGYSPTSPGYSPTSPTYSPSSPGYSPTSPAYSPTSPSY 1600
1601 SPTSPSYSPTSPSYSPTSPSYSPTSPSYSPTSPSYSPTSPAYSPTSPAYS 1650
1651 PTSPAYSPTSPSYSPTSPSYSPTSPSYSPTSPSYSPTSPSYSPTSPAYSP 1700
1701 TSPGYSPTSPSYSPTSPSYGPTSPSYNPQSAKYSPSIAYSPSNARLSPAS 1750
1751 PYSPTSPNYSPTSPSYSPTSPSYSPSSPTYSPSSPYSSGASPDYSPSAGY 1800
1801 SPTLPGYSPSSTGQYTPHEGDKKDKTGKKDASKDDKGNP 1839
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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