 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P59510 from www.uniprot.org...
The NucPred score for your sequence is 0.82 (see score help below)
1 MWVAKWLTGLLYHLSLFITRSWEVDFHPRQEALVRTLTSYEVVIPERVNE 50
51 FGEVFPQSHHFSRQKRSSEALEPMPFRTHYRFTAYGQLFQLNLTADASFL 100
101 AAGYTEVHLGTPERGAWESDAGPSDLRHCFYRGQVNSQEDYKAVVSLCGG 150
151 LTGTFKGQNGEYFLEPIMKADGNEYEDGHNKPHLIYRQDLNNSFLQTLKY 200
201 CSVSESQIKETSLPFHTYSNMNEDLNVMKERVLGHTSKNVPLKDERRHSR 250
251 KKRLISYPRYIEIMVTADAKVVSAHGSNLQNYILTLMSIVATIYKDPSIG 300
301 NLIHIVVVKLVMIHREEEGPVINFDGATTLKNFCSWQQTQNDLDDVHPSH 350
351 HDTAVLITREDICSSKEKCNMLGLSYLGTICDPLQSCFINEEKGLISAFT 400
401 IAHELGHTLGVQHDDNPRCKEMKVTKYHVMAPALSFHMSPWSWSNCSRKY 450
451 VTEFLDTGYGECLLDKPDEEIYNLPSELPGSRYDGNKQCELAFGPGSQMC 500
501 PHINICMHLWCTSTEKLHKGCFTQHVPPADGTDCGPGMHCRHGLCVNKET 550
551 ETRPVNGEWGPWEPYSSCSRTCGGGIESATRRCNRPEPRNGGNYCVGRRM 600
601 KFRSCNTDSCPKGTQDFREKQCSDFNGKHLDISGIPSNVRWLPRYSGIGT 650
651 KDRCKLYCQVAGTNYFYLLKDMVEDGTPCGTETHDICVQGQCMAAGCDHV 700
701 LNSSAKIDKCGVCGGDNSSCKTITGVFNSSHYGYNVVVKIPAGATNVDIR 750
751 QYSYSGQPDDSYLALSDAEGNFLFNGNFLLSTSKKEINVQGTRTVIEYSG 800
801 SNNAVERINSTNRQEKEILIEVLCVGNLYNPDVHYSFNIPLEERSDMFTW 850
851 DPYGPWEGCTKMCQGLQRRNITCIHKSDHSVVSDKECDHLPLPSFVTQSC 900
901 NTDCELRWHVIGKSECSSQCGQGYRTLDIHCMKYSIHEGQTVQVDDHYCG 950
951 DQLKPPTQELCHGNCVFTRWHYSEWSQCSRSCGGGERSRESYCMNNFGHR 1000
1001 LADNECQELSRVTRENCNEFSCPSWAASEWSECLVTCGKGTKQRQVWCQL 1050
1051 NVDHLSDGFCNSSTKPESLSPCELHTCASWQVGPWGPCTTTCGHGYQMRD 1100
1101 VKCVNELASAVLEDTECHEASRPSDRQSCVLTPCSFISKLETALLPTVLI 1150
1151 KKMAQWRHGSWTPCSVSCGRGTQARYVSCRDALDRIADESYCAHLPRPAE 1200
1201 IWDCFTPCGEWQAGDWSPCSASCGHGKTTRQVLCMNYHQPIDENYCDPEV 1250
1251 RPLMEQECSLAACPPAHSHFPSSPVQPSYYLSTNLPLTQKLEDNENQVVH 1300
1301 PSVRGNQWRTGPWGSCSSSCSGGLQHRAVVCQDENGQSASYCDAASKPPE 1350
1351 LQQCGPGPCPQWNYGNWGECSQTCGGGIKSRLVICQFPNGQILEDHNCEI 1400
1401 VNKPPSVIQCHMHACPADVSWHQEPWTSCSASCGKGRKYREVFCIDQFQR 1450
1451 KLEDTNCSQVQKPPTHKACRSVRCPSWKANSWNECSVTCGSGVQQRDVYC 1500
1501 RLKGVGQVVEEMCDQSTRPCSQRRCWSQDCVQHKGMERGRLNCSTSCERK 1550
1551 DSHQRMECTDNQIRQVNEIVYNSSTISLTSKNCRNPPCNYIVVTADSSQC 1600
1601 ANNCGFSYRQRITYCTEIPSTKKHKLHRLRPIVYQECPVVPSSQVYQCIN 1650
1651 SCLHLATWKVGKWSKCSVTCGIGIMKRQVKCITKHGLSSDLCLNHLKPGA 1700
1701 QKKCYANDCKSFTTCKEIQVKNHIRKDGDYYLNIKGRIIKIYCADMYLEN 1750
1751 PKEYLTLVQGEENFSEVYGFRLKNPYQCPFNGSRREDCECDNGHLAAGYT 1800
1801 VFSKIRIDLTSMQIKTTDLLFSKTIFGNAVPFATAGDCYSAFRCPQGQFS 1850
1851 INLSGTGMKISSTAKWLTQGSYTSVSIRRSEDGTRFFGKCGGYCGKCLPH 1900
1901 MTTGLPIQVI 1910
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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