 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9UNS1 from www.uniprot.org...
The NucPred score for your sequence is 0.92 (see score help below)
1 MDLHMMNCELLATCSALGYLEGDTYHKEPDCLESVKDLIRYLRHEDETRD 50
51 VRQQLGAAQILQSDLLPILTQHHQDKPLFDAVIRLMVNLTQPALLCFGNL 100
101 PKEPSFRHHFLQVLTYLQAYKEAFASEKAFGVLSETLYELLQLGWEERQE 150
151 EDNLLIERILLLVRNILHVPADLDQEKKIDDDASAHDQLLWAIHLSGLDD 200
201 LLLFLASSSAEEQWSLHVLEIVSLMFRDQNPEQLAGVGQGRLAQERSADF 250
251 AELEVLRQREMAEKKTRALQRGNRHSRFGGSYIVQGLKSIGERDLIFHKG 300
301 LHNLRNYSSDLGKQPKKVPKRRQAARELSIQRRSALNVRLFLRDFCSEFL 350
351 ENCYNRLMGSVKDHLLREKAQQHDETYYMWALAFFMAFNRAASFRPGLVS 400
401 ETLSVRTFHFIEQNLTNYYEMMLTDRKEAASWARRMHLALKAYQELLATV 450
451 NEMDISPDEAVRESSRIIKNNIFYVMEYRELFLALFRKFDERCQPRSFLR 500
501 DLVETTHLFLKMLERFCRSRGNLVVQNKQKKRRKKKKKVLDQAIVSGNVP 550
551 SSPEEVEAVWPALAEQLQCCAQNSELSMDSVVPFDAASEVPVEEQRAEAM 600
601 VRIQDCLLAGQAPQALTLLRSAREVWPEGDVFGSQDISPEEEIQLLKQIL 650
651 SAPLPRQQGPEERGAEEEEEEEEEEEEELQVVQVSEKEFNFLDYLKRFAC 700
701 STVVRAYVLLLRSYQQNSAHTNHCIVKMLHRLAHDLKMEALLFQLSVFCL 750
751 FNRLLSDPAAGAYKELVTFAKYILGKFFALAAVNQKAFVELLFWKNTAVV 800
801 REMTEGYGSLDDRSSSRRAPTWSPEEEAHLRELYLANKDVEGQDVVEAIL 850
851 AHLNTVPRTRKQIIHHLVQMGLADSVKDFQRKGTHIVLWTGDQELELQRL 900
901 FEEFRDSDDVLGHIMKNITAKRSRARIVDKLLALGLVAERRELYKKRQKK 950
951 LASSILPNGAESLKDFCQEDLEEEENLPEEDSEEEEEGGSEAEQVQGSLV 1000
1001 LSNENLGQSLHQEGFSIPLLWLQNCLIRAADDREEDGCSQAVPLVPLTEE 1050
1051 NEEAMENEQFQQLLRKLGVRPPASGQETFWRIPAKLSPTQLRRAAASLSQ 1100
1101 PEEEQKLQPELQPKVPGEQGSDEEHCKEHRAQALRALLLAHKKKAGLASP 1150
1151 EEEDAVGKEPLKAAPKKRQLLDSDEEQEEDEGRNRAPELGAPGIQKKKRY 1200
1201 QIEDDEDD 1208
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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