 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q7Z020 from www.uniprot.org...
The NucPred score for your sequence is 0.69 (see score help below)
1 MTSGDKETPKREDFASALRFLMGGCAREPEMTAMAPLNLPKKWARILRMS 50
51 STPKIPIVDYLEAAESGNLDDFKRLFMADNSRIALKDAKGRTAAHQAAAR 100
101 NRVNILRYIRDQNGDFNAKDNAGNTPLHIAVESDAYDALDYLLSIPVDTG 150
151 VLNEKKQAPVHLATELNKVKSLRVMGQYRNVIDIQQGGEHGRTALHLAAI 200
201 YDHEECARILITEFDACPRKPCNNGYYPIHEAAKNASSKTMEVFFQWGEQ 250
251 RGCTREEMISFYDSEGNVPLHSAVHGGDIKAVELCLKSGAKISTQQHDLS 300
301 TPVHLACAQGAIDIVKLMFEMQPMEKRLCLSCTDVQKMTPLHCASMFDHP 350
351 DIVSYLVAEGADINALDKEHRSPLLLAASRSGWKTVHLLIRLGACISVKD 400
401 AAARNVLHFVIMNGGRLTDFAEQVANCQTQAQLKLLLNEKDSMGCSPLHY 450
451 ASRDGHIRSLENLIRLGACINLKNNNNESPLHFAARYGRYNTVRQLLDSE 500
501 KGSFIINESDGAGMTPLHISSQQGHTRVVQLLLNRGALLHRDHTGRNPLQ 550
551 LAAMSGYTETIELLHSVHSHLLDQVDKDGNTALHLATMENKPHAISVLMS 600
601 MGCKLVYNVLDMSAIDYAIYYKYPEAALAMVTHEERANEVMALRSDKHPC 650
651 VTLALIASMPKVFEAVQDKCITKANCKKDSKSFYIKYSFAFLQCPFMFAK 700
701 IDEKTGESITTASPIPLPALNTMVTHGRVELLAHPLSQKYLQMKWNSYGK 750
751 YFHLANLLIYSIFLVFVTIYSSLMMNNIELKAGDNKTMSQYCNMGWEQLT 800
801 MNLSQNPSVASQIRLDSCEERINRTTAILFCAVVIVVYILLNSMRELIQI 850
851 YQQKLHYILETVNLISWVLYISALVMVTPAFQPDGGINTIHYSAASIAVF 900
901 LSWFRLLLFLQRFDQVGIYVVMFLEILQTLIKVLMVFSILIIAFGLAFYI 950
951 LLSKIIDPQPNHLSFSNIPMSLLRTFSMMLGELDFVGTYVNTYYRDQLKV 1000
1001 PMTSFLILSVFMILMPILLMNLLIGLAVGDIESVRRNAQLKRLAMQVVLH 1050
1051 TELERKLPHVWLQRVDKMELIEYPNETKCKLGFCDFILRKWFSNPFTEDS 1100
1101 SMDVISFDNNDDYINAELERQRRKLRDISRMLEQQHHLVRLIVQKMEIKT 1150
1151 EADDVDEGISPNELRSVVGLRSAGGNRWNSPRVRNKLRAALSFNKSM 1197
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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