 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8CFC2 from www.uniprot.org...
The NucPred score for your sequence is 0.91 (see score help below)
1 MSSESDDKRARTRSKTLRGPPETTGADLSCPTPGCTGSGHVRGKYSRHRS 50
51 LQSCPLAKKRKLEDAETEHLVSKRKSHPLRLALDEGYRMDSDGSEDAEVK 100
101 DVSVSDESEGPLEEAEAEMSGQEEIHHPQTAEGKSLIKPHFDSNPTSSPS 150
151 GFSKSSYSSYQGIIATSLLNLGQIAEEALVKEDSVSVAKLSPTVVHQLQD 200
201 EAAMGVNSDEGEKDLFIQPEDVEEVIEVTSERSQEPCPQSLKDMVSEESS 250
251 KQKGVLGHEEEGEEEEEDEEEEDEEEEEEGEEGEEEEEEEEEEEEEEDEE 300
301 EEEEEEEAAPNVIFGEDTSHTSVQKASPEFRGPELSSPKPEYSVIVEVRS 350
351 DDDKDEDSRSQKSAVTDESEMYDMMTRGNLGLLEQAIALKAEQVRAVCES 400
401 GCPPAEQGHLGPGEPGKMAKPLDVVRKSCYSKDPSRVEKREIKCPTPGCD 450
451 GTGHVTGLYPHHRSLSGCPHKDRIPPEILAMHENVLKCPTPGCTGQGHVN 500
501 SNRNTHRSLSGCPIAAAEKLAKSHEKQQLQTGDPPKNNSNSDRILRPMCF 550
551 VKQLEVPPYGSYRPNVAPATPRANLAKELEKFSKVTFDYASFDAQVFGKR 600
601 MLAPKIQTSETSPKAFQCFDYSHDAEAAHMAATAILNLSTRCWEMPENLS 650
651 TKPQDLPSKAVDIEVDENGTLDLSMHKHRKRENTFPSSSSCSSSPGVKSP 700
701 DVSQRQSSTSAPSSSMTSPQSSQASRQDEWDRPLDYTKPSRLREEEPEES 750
751 EPAAHSFASSEADDQEVSEENFEERKYPGEVTLTNFKLKFLSKDIKKELL 800
801 TCPTPGCDGSGHITGNYASHRSLSGCPLADKSLRNLMAAHSADLKCPTPG 850
851 CDGSGHITGNYASHRSLSGCPRAKKSGLKVAPTKDDKEDPELMKCPVPGC 900
901 VGLGHISGKYASHRSASGCPLAARRQKEGALNGSSFSWKSLKNEGPTCPT 950
951 PGCDGSGHANGSFLTHRSLSGCPRATFAGKKGKLSGDEILSPKFKTSDVL 1000
1001 ENDEEIKQLNQEIRDLNESNSEMEAAMVQLQSQISSMEKNLKNIEEENKL 1050
1051 IEEQNEALFLELSGLSQALIQSLANIRLPHMEPICEQNFDAYVNTLTDMY 1100
1101 SNQDCYQNPENKGLLETIKQAVRGIQV 1127
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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