 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9UMS6 from www.uniprot.org...
The NucPred score for your sequence is 0.93 (see score help below)
1 MGTGDFICISMTGGAPWGFRLQGGKEQKQPLQVAKIRNQSKASGSGLCEG 50
51 DEVVSINGNPCADLTYPEVIKLMESITDSLQMLIKRPSSGISEALISENE 100
101 NKNLEHLTHGGYVESTTLQIRPATKTQCTEFFLAPVKTEVPLAENQRSGP 150
151 DCAGSLKEETGPSYQRAPQMPDSQRGRVAEELILREKVEAVQPGPVVELQ 200
201 LSLSQERHKGASGPLVALPGAEKSKSPDPDPNLSHDRIVHINSIPTNEKA 250
251 DPFLRSSKIIQISSGRELRVIQESEAGDAGLPRVEVILDCSDRQKTEGCR 300
301 LQAGKECVDSPVEGGQSEAPPSLVSFAVSSEGTEQGEDPRSEKDHSRPHK 350
351 HRARHARLRRSESLSEKQVKEAKSKCKSIALLLTDAPNPNSKGVLMFKKR 400
401 RRRARKYTLVSYGTGELEREADEEEEGDKEDTCEVAFLGASESEVDEELL 450
451 SDVDDNTQVVNFDWDSGLVDIEKKLNRGDKMEMLPDTTGKGALMFAKRRE 500
501 RMDQITAQKEEDKVGGTPSREQDAAQTDGLRTTTSYQRKEEESVRTQSSV 550
551 SKSYIEVSHGLGHVPQQNGFSGTSETANIQRMVPMNRTAKPFPGSVNQPA 600
601 TPFSPTRNMTSPIADFPAPPPYSAVTPPPDAFSRGVSSPIAGPAQPPPWP 650
651 QPAPWSQPAFYDSSERIASRDERISVPAKRTGILQEAKRRSTTKPMFTFK 700
701 EPKVSPNPELLSLLQNSEGKRGTGAGGDSGPEEDYLSLGAEACNFMQSSS 750
751 AKQKTPPPVAPKPAVKSSSSQPVTPVSPVWSPGVAPTQPPAFPTSNPSKG 800
801 TVVSSIKIAQPSYPPARPASTLNVAGPFKGPQAAVASQNYTPKPTVSTPT 850
851 VNAVQPGAVGPSNELPGMSGRGAQLFAKRQSRMEKYVVDSDTVQAHAARA 900
901 QSPTPSLPASWKYSSNVRAPPPVAYNPIHSPSYPLAALKSQPSAAQPSKM 950
951 GKKKGKKPLNALDVMKHQPYQLNASLFTFQPPDAKDGLPQKSSVKVNSAL 1000
1001 AMKQALPPRPVNAASPTNVQASSVYSVPAYTSPPSFFAEASSPVSASPVP 1050
1051 VGIPTSPKQESASSSYFVAPRPKFSAKKSGVTIQVWKPSVVEE 1093
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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