| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q753V5 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MQRTGDGERPRFFQQDLDVIPDDKGSDLFIQTAEGPDGHVDDEVIEDKTR 50
51 FITNLKEVLGALPDDILEGYWNSYGASKDGLSKAIQQHFEGKETKGCSDA 100
101 HDDLNTETQNSQNTIVNGHVSNQIKRASEGGLPILKRKKQLCCWRRFLGS 150
151 TQVNAMATRPTAQPLKYGSELLIRRTSGQPNNSGLRSRKKPGFSQYVRFC 200
201 DATSSRELGRLPEDISEILHTLLQTPGVEFKATMIFCNSKRLSVGDLFVV 250
251 RLDCFVTSLLFDPALPGKAEDEQFQQRNRALMLLFKNLNMTPLAEGADLV 300
301 PEKPEFYDLEEDESITDATVNSPTASDDYMDLNQLRNFYRSTQESASIFK 350
351 LRETTPPVDKFQLELRRYQKQGLTWMLLREREHAILEPGSQDALADGPMD 400
401 PMWRMFKWPRDTSWDVSRGTTYVSLEADIPDKFYANLHTGEFSLVKPISK 450
451 SILKGGILADEMGLGKTISILALITMVPSDTKHLLTTAQEKPPVGHLSLE 500
501 LGISTVKPYTASTTLIVVPMSLLPQWRNEFVRVNDGNGLYCEVYYAGNVS 550
551 NLRTLLVKQKSPPSVVLTTYGVVQTEWSKLQQFDYEASNEGLFSVEFFRI 600
601 ILDEGHNIRNRTTKTSKAVMALTSRRKWVLTGTPIMNRLDDLFSLIKFMN 650
651 FEPWCKIDYWRQFVSDPFEKKDYSSALEVIQAVMGPILLRRTKNMKDEDG 700
701 NPLVQLPPKEVVIEMIRFSDTEAGLYKYFLSKAEHSVKESLARGDLLKKY 750
751 STILLHILRLRQVCCHFKLLGSQDENDEDLKNMKLINDIPDISTLLGEDS 800
801 QSPGSSSEGMPDFIEDFKTKYPNSDALKDLECSICTCEAISPLTSVVFTR 850
851 CGHPFCESCLLEYIQFQNKKGSETICPNCRAAVESRYLLKLEDINGKLEP 900
901 VPYSNTKKSSKIVALIRHLKHLQDTSANEQVVVFSQFSSYLDILENELRQ 950
951 SFASDICEIYKFDGRLDLKERSNVLAKFTEKSLVKMKVLLLSLKAGGVGL 1000
1001 NLTCASHAFIMDPWWSPGMEDQAMDRIHRIGQSNTVKIYRFIVENSIEEK 1050
1051 MLRIQEKKRSLGEFVDADEEERRRSRIEEIKMLFA 1085
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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