 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6BEA0 from www.uniprot.org...
The NucPred score for your sequence is 0.52 (see score help below)
1 MAFHNRRWNFTFSCCVVVLLLPLVAARPQQPSAATRVHEEYSTFRVENTE 50
51 WTFNHLAVDHRNGNVYLGAVNRIYKLSPGLDIQVSHQTGPDEDNRNCYPP 100
101 RIVQPCSEPLTLTNNVNKMLLMDYRENRLLACGSLYQGICKLLRLDDLFK 150
151 LGEPFHKKEHYLSGVNESGSVFGVIVSYGDASPDKLFVATAVDGRPEYFP 200
201 TISSRKLTRNSEEDGMFAYVFHDEFVASMIKIPSDTFTVVPDFDIYYVYG 250
251 FSSGNFVYFLTLQPEMGGGPTTGSSSAGREQVYTSKLVRLCKDDTAFNSY 300
301 VEVPLGCVKGGVEYRLLQAAYLSKAGTILARSLGIGPDDDILYAVFSKGQ 350
351 KRRPKESSQESALCVFTLKEINERIKDRLQSCYKGEGTLDLAWLKVKDIS 400
401 CSSALLTIDDNFCGLDMNAPLGVSEMVRGIPLFSESKDKMTSVIAYVYKN 450
451 HSLAFVGTRGGRLKKIRVDGPTYGALQYETIQVVDNGPILRDMAFSSDQH 500
501 FLYVMSESQLTRVPVEACEQYSSCNECLGSGDPHCGWCVLHSMCTRKEKC 550
551 ERSSEPRRFASNIKQCVRLSVHPNNISVSQYSVMLVLEAHNVPELSAGVN 600
601 CTFEDLAEMDGLVEGNRITCSSPAEKEVPRIIVDQGDHQIVQLYLKSKET 650
651 GLAFANTSFVFYNCSVHKSCLSCVGSPYQCHWCKYRHTCTHDPSSCSFQE 700
701 GRVKQPEECPQLLPADRILVPVNVVKPITLRAKNLPQPQSGQRGYECVLT 750
751 IQGVEQRVPALRFNSSSVQCQNTSYMYDGMEMSSLPVDLTVIWNGDFSID 800
801 NPAQNKVHLYKCDARRESCGLCLKADPLFGCVWCKGENRCSLKQHCSYPQ 850
851 SMWLEHNGINSKCTHPRITKITPLRGPREGGTLVTIRGENLGLEFSEIKD 900
901 HVKVADVECTPVPEGYIPAEQIVCEMGKAERSQFAGNVQVCVGECRPEFM 950
951 AKSSKYYYFVIPQLLSLKPSRGPISGGTIVNITGGNLDAGSNVSIMFKDQ 1000
1001 KCTYQRRGGQWITCRSHASMQGYGNVSVSVYVDKAHIHKDLKFEYVEDPT 1050
1051 ITKLEPEWSIFSGNTPLTVSGTNLDIIHTPLIRAKYKNLETINICQVLSP 1100
1101 TTMQCMAPELPYSISKHKDVPERPDEFGFILDNVQSVLALNNTNFVYYPN 1150
1151 PVFEPLSVSGVQELKPGSPIILKGRNFLPPTPGGNGKLNYTVLIGDKPCA 1200
1201 LTVSDTQLLCESPNLTGRHKVLARVGGIEFSPGVVHITSDSPLSSTAVIS 1250
1251 IAGAGGLLIFFIVIVLIAYKRKSRESDLTLKRLQMQMDNLESRVALECKE 1300
1301 AFAELQTDIHELTSDLDGAGIPFLDYRTYTMRVLFPGIEEHPVLRDLEVP 1350
1351 GYRQEQVEKGLKLFGQLINNKVFLLSFIRTLESQRGFSMRDRGNVASLIM 1400
1401 TVLQSKLEYATDVLKHLLSDLIDKNLESKNHPKLLLRRTESVAEKMLTNW 1450
1451 FTFLLYKFLKECAGEPLFSLFCAIKQQMEKGPIDSITGEARYSLSEDKLI 1500
1501 RQQIDYKTLVVNCMHPDNEKSPEVQVKVLNCDTVSQVKEKILDAIYKNVP 1550
1551 YSHRPKASDMDLEWRQGRVVRVILQDEDVTTKIEADWKRLNMLSHYQVTD 1600
1601 NAVVALVPKQVTAYNSVNNSTVSRTSASKYENMIKYTGSPDSLRSRTPMI 1650
1651 TPDLESGVKVWHLVKNHEHGDQKEGDRGSKMVSEIYLTRLLATKGTLQKF 1700
1701 VDDLFETIFSTAHRGSALPLAIKYMFDFLDEQADKHNIHDPHVRHTWKSN 1750
1751 CLPLRFWVNVIKNPQFVFDIHKSSITDACLSVVAQTFMDSCSTSEHRLGK 1800
1801 DSPSNKLLYAKDIPSYKSWVERYYSDISKMPAISDQDMNAYLAEQSRMHM 1850
1851 NEFNTMSSLSEIYSYIGKYTEEIVSALEQDDGARKQRLAYKLEQVVAFMS 1900
1901 LES 1903
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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