| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q5SXJ3 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MSSVLSDYTIGGVKIHFPCRAYPAQLAMMNSIVRGLNSSQHCLLESPTGS 50
51 GKSLALLCSALAWQQSLSEKPVDEGLNKKPEAPPSCSCACHSKNFTYSDT 100
101 NLDTSPHFNSPSKPSSGRNGVSTPCQDSPEKNTLAAKLSAKKQASIHRDE 150
151 DDDFQVEKKRIRPLETTQQIRKRHCLEKDVHHVDARLASEKRVKPESPIG 200
201 KSFSDRKDSFQNVDGLCSRCCCSAKQGNNQEPANTVKKDHGGQCKRPKIY 250
251 FGTRTHKQIAQITRELRKTAYSGVPMTILSSRDHSCVHPEVVGNFNRKEK 300
301 CMELLDGKHGKSCYFYHGVHKISNQQTLQHLQGMSRAWDIEELVSLGRKL 350
351 KACPYYTARELIEDADIVFCPYNYLLDSQIRETMDIKLKGQVVILDEAHN 400
401 IEDCARESASYSVTEVQLRFARDELDSLINGNIRKKSHEPLRDVCYNLIN 450
451 WLETNSKHLVERGYESSCKIWSGNEMLLNLYRMGITTATFPVLQRHLSAV 500
501 LQKEEKVTPIHGKEEAIQIPIISASTQVVLKGLFMVLDYLFRENSRFADD 550
551 YKVAIQQTYSWTNQIAIFDKTGVLAVPKNKKHSRQKIGVNALNFWCLNPA 600
601 VAFSDINDKVRTIVLTSGTLSPLKSFSSELGVTFSIQLEANHVISNSQVW 650
651 VGTVGSGPKGRNLCATFQHTETFEFQDEVGMLLLSVCQTVSQGILCFLPS 700
701 YKLLEKLRERWIFTGLWHSLESVKTVIAEPQGGEKTDFDELLQVYYDAIK 750
751 FKGEKDGALLIAVCRGKVSEGLDFSDDNARAVITVGIPFPNVKDLQVELK 800
801 RQYNDHHSKSRGLLPGRQWYEIQAYRALNQALGRCIRHKNDWGALILVDD 850
851 RFNNNPNRYISGLSKWVRQQIQHHSSFASALESLTEFSRRHQKVTNRSKK 900
901 DEKCTKDNEPTLEVACLEDSTFTSVSESSHQSPENSTEEAEVCVQELQCP 950
951 QVATKSPSVASHGVSRRKKSDPGLRGESLQTMKTEKNEISRSSSPTFGKQ 1000
1001 TEPVNWPIFNSLRRHFNSKVKNCTPVLKSSKNRAPGSSTFNKTALPLTGN 1050
1051 CVPSNETADTSLGPCLQSEVIISPVKIEATPATNYSKQVFCCEKDLLPDT 1100
1101 ELSPGTEEAKCPSSNKAAETEVDDDSECFTPELFDPVDTNEENGELVETD 1150
1151 RSSHSSDCFSAEELFETATGFGQK 1174
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.) |
Go back to the NucPred Home Page.