 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q95UN8 from www.uniprot.org...
The NucPred score for your sequence is 0.94 (see score help below)
1 MPSQVSRGLDTTNMLPISEEQQLQQQQQQQQLEQLHHPQIPEIPIPDLEQ 50
51 VETQVGDGSLWTALYDYDAQGEDELTLRRGEIVVVLSTDSEVSGDVGWWT 100
101 GKIGDKVGVFPKDFVTDEDPLQLNVSSAIGDIQPHEIEYNELDIKEVIGS 150
151 GGFCKVHRGYYDGEEVAIKIAHQTGEDDMQRMRDNVLQEAKLFWALKHEN 200
201 IAALRGVCLNTKLCLVMEYARGGSLNRILAGKIPPDVLVNWAIQIARGMN 250
251 YLHNEAPMSIIHRDLKSSNVLIYEAIEGNHLQQKTLKITDFGLAREMYNT 300
301 QRMSAAGTYAWMPPEVISVSTYSKFSDVWSYGVLLWELITGETPYKGFDP 350
351 LSVAYGVAVNTLTLPIPKTCPETWGALMKSCWQTDPHKRPGFKEILKQLE 400
401 SIACSKFTLTPQESFHYMQECWRKEIAGVLHDLREKEKELRNKEEQLLRV 450
451 QNEQREKANLLKIREQNLRERERVLIERELVMLQPVPSKRKHKKGKKNKP 500
501 LQISLPTGFRHTITAVRDKAEQPGSPSFSGLRIVALTDGHKGKTWGPSTM 550
551 HQRERSLLPSQLSGGQPEWPAQTSTHSSFSKSAPNLDKKQQQQNQQQVAS 600
601 LTPPPGLGILGGSGGAGGTPATPLLYPGIPIILTRPNNNNIGNCKAITTT 650
651 ITTTTTTTTNNNNNNNNSISANNNNQLNNISTINSNNNNNQTNLTSQPNT 700
701 IIVLQNGRNNSNSSTTSQSPAKIYHRARSQEYGLDHPLAYQPPPLYLVTD 750
751 DSSETDTVASPTGCFHFLKSGNSSAASGAVHLHRFGGSLGNSPAVGRKKH 800
801 SLDSSSHHPPANGSNSFALPNQLTLPSEDNNTYDHAFYRDVIKKMSMASS 850
851 ERVNSKSSGDLTMYNSSTPLTARDCDDAEEAFEGGRFQRNFSGSQFPRHC 900
901 FFTRQEEEGEAEDEDAVAAEVDTADADADDECQVPASQMRQNSTTSRKSS 950
951 VTFQSVSFEEPDFVATPRTTARSDLYTSSASISFATYRSASPSLSSSSTT 1000
1001 ASASPSIASTEAVNGYHMQENSILNTRRMQDVQPHPDVIKLRAQEQRQQT 1050
1051 KNQKKQRPKHITKSKSVEAPVEGQHHEHDDHNDPQHQHHSAGSSKIRALF 1100
1101 NLFTRSRKKYSKLAEHNMVGGPEFCAIDPYQTDLAMGGSSRSLKRKGKKP 1150
1151 QTQSCEQLERC 1161
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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