| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q5REF4 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MTRRCMPARPGFPSSPAPGSSPPRCHLRPGSTAHAAAGKRTESPGDRKQS 50
51 IIDFFKPASKQGRHMLDSPQKSNIKYGGSRLSITGTERFERKLSSPKKSK 100
101 TKRVPPEKSPIIEAFMKGVKEHHEDHGIHESCRPCVSLASKYLAKGTNIY 150
151 VPSSYHLAKEMKSLKKNHRSPERRKSLFIHENNEKNDRDRGKTNADSKKQ 200
201 TTVAEADIFKNSSRSLSSRSSLSRHHPGESPLGAKFQLSLASYCRERELK 250
251 RLRKEQMEQRINSENSFSEASNLSLKSSSIERKYKPRQEQRKQNDVIPGK 300
301 NNLSNVENGHLSRKRSSSDSWEPTSAGSKQNKFPEKRKRNSVDSDLKSTR 350
351 ESMIPKARESFLEKRPDGPHQKEKFIKHIALKTPGDVLRLEDISKEPNDE 400
401 TDCSSAGLAPSNSGSSGHHSTRNSDQIRVAGTKETKMQKPHLPLSQEKSA 450
451 IKKASNLQKNKTTSSMTKEKETKLPLLSHVPSAGSSLVPLNAKNCALPVS 500
501 KKDKERSSSKECSGHSTESTKHKEHKAKTNKADSNVSSGKISGGPLCSEY 550
551 GAPTKSPPAALEVVPCVPSPAAPSDKAPSERESSGNSNAGSSALKRKLRG 600
601 DFDSDEESLGYNLDSDEEEETLKSLEEIMALNFNQTPATTGKPPALSKEL 650
651 RSQSSDYTGHDHPGTYTNTLERLVKEMEDTQRLDELQKQLQEDIRQGRGI 700
701 KSPIRIGEEDSTDDEDGLLEEHKEFLKKFSVTIDAIPDHHPGEEIFNFLN 750
751 SGKIFNQYTLDLRDSGFIGQSAVEKLILKSGKTDQIFLTTQGFLTSAYHY 800
801 VQCPVPVLKWLFRMMSVHTDCIVSVQILSTLMEITIRNDTFSDSPVWPWI 850
851 PSLSDVAAVFFNMGIDFRSLFPLENLQPDFNEDYLVSETQTTSRGKESED 900
901 SSYKPIFSTLPETNILNVVKFLGLCTSIHPEGYQDREIMLLILMLFKMSL 950
951 EKQLKQIPLVDFQSLLINLMKNIRDWNTKVPELCLGINELSSHPHNLLWL 1000
1001 VQLVPNWTSRGRQLRQCLSLVIISKLLDEKHEDVPNASNLQVSVLHRYLV 1050
1051 QMKPSDLLKKMVLKKKAEQPDGIIDDSLHLELEKQAYYLTYILLHLVGEV 1100
1101 SCSHSFSSGQRKHFVLLCGALEKHVKCDIREDARLFYRTKVKDLVARIHG 1150
1151 KWQEIIQNCRPTQGQLHDFWVPDS 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.) |
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