 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8NB49 from www.uniprot.org...
The NucPred score for your sequence is 0.34 (see score help below)
1 MQMVPSLPPASECAGEEKRVGTRTVFVGNHPVSETEAYIAQRFCDNRIVS 50
51 SKYTLWNFLPKNLFEQFRRIANFYFLIIFLVQVTVDTPTSPVTSGLPLFF 100
101 VITVTAIKQGYEDCLRHRADNEVNKSTVYIIENAKRVRKESEKIKVGDVV 150
151 EVQADETFPCDLILLSSCTTDGTCYVTTASLDGESNCKTHYAVRDTIALC 200
201 TAESIDTLRAAIECEQPQPDLYKFVGRINIYSNSLEAVARSLGPENLLLK 250
251 GATLKNTEKIYGVAVYTGMETKMALNYQGKSQKRSAVEKSINAFLIVYLF 300
301 ILLTKAAVCTTLKYVWQSTPYNDEPWYNQKTQKERETLKVLKMFTDFLSF 350
351 MVLFNFIIPVSMYVTVEMQKFLGSFFISWDKDFYDEEINEGALVNTSDLN 400
401 EELGQVDYVFTDKTGTLTENSMEFIECCIDGHKYKGVTQEVDGLSQTDGT 450
451 LTYFDKVDKNREELFLRALCLCHTVEIKTNDAVDGATESAELTYISSSPD 500
501 EIALVKGAKRYGFTFLGNRNGYMRVENQRKEIEEYELLHTLNFDAVRRRM 550
551 SVIVKTQEGDILLFCKGADSAVFPRVQNHEIELTKVHVERNAMDGYRTLC 600
601 VAFKEIAPDDYERINRQLIEAKMALQDREEKMEKVFDDIETNMNLIGATA 650
651 VEDKLQDQAAETIEALHAAGLKVWVLTGDKMETAKSTCYACRLFQTNTEL 700
701 LELTTKTIEESERKEDRLHELLIEYRKKLLHEFPKSTRSFKKAWTEHQEY 750
751 GLIIDGSTLSLILNSSQDSSSNNYKSIFLQICMKCTAVLCCRMAPLQKAQ 800
801 IVRMVKNLKGSPITLSIGDGANDVSMILESHVGIGIKGKEGRQAARNSDY 850
851 SVPKFKHLKKLLLAHGHLYYVRIAHLVQYFFYKNLCFILPQFLYQFFCGF 900
901 SQQPLYDAAYLTMYNICFTSLPILAYSLLEQHINIDTLTSDPRLYMKISG 950
951 NAMLQLGPFLYWTFLAAFEGTVFFFGTYFLFQTASLEENGKVYGNWTFGT 1000
1001 IVFTVLVFTVTLKLALDTRFWTWINHFVIWGSLAFYVFFSFFWGGIIWPF 1050
1051 LKQQRMYFVFAQMLSSVSTWLAIILLIFISLFPEILLIVLKNVRRRSARR 1100
1101 NLSCRRASDSLSARPSVRPLLLRTFSDESNVL 1132
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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