 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q5DQR4 from www.uniprot.org...
The NucPred score for your sequence is 0.69 (see score help below)
1 MKKFNFRKVLDGLTASSPGSGSSSGSNSGGAGSGSVHPGGTAGLPREEIQ 50
51 ESLTSDYFQICKTVRHGFPYQPTALAFDPVQKILAIGTRTGAIRILGRPG 100
101 VDCYCQHESGAAVLQLQFLINEGALVSASSDDTLHLWNLRQKRPAILHSL 150
151 KFNRERITYCHLPFQSKWLYVGTERGNTHIVNIESFILSGYVIMWNKAIE 200
201 LSTKTHPGPVVHLSDSPRDEGKLLIGYENGTVVFWDLKSKRAELRVYYDE 250
251 AIHSIDWHHEGKQFMCSHSDGSLTLWNLKSPSRPFQTTVPHGKSQREGRK 300
301 SESCKPILKVEYKTCRNSEPFIIFSGGLSYDKACRRPSLTIMHGKAITVL 350
351 EMDHPIVEFLTLCETPYPNEFQEPYAVAVLLEKDLIVVDLTQTNFPIFEN 400
401 PYPMDIHESPVTCTAYFADCPPDLILVLYSIGVKHKKQGYSNKEWPVSGG 450
451 AWNLGAQTYPEIIITGHADGTIKFWDASAMTLQMLYKLKTSKVFEKQKAG 500
501 EGKQTCELVEEDPFAVQMIYWCPESRIFCVSGVSAYVIIYKFSRHEVTTE 550
551 IVSLEVRLQCDVEDIITPEPETSPPFPDLSSQLPPSRSLSGSTNTVSSEG 600
601 VTKDSIPCLSVKTRPVRMPPGYQADLVIQLVWVDGEPPQQITSLSISSAY 650
651 GIVAFGNCTGLVVVDFIQKTVLLSMGTIDLYRSSDLYQRQPRSPRKNRQF 700
701 IADNFCMRGLSNFYPDLTKRIRTSYQSLTELNDSPVPLELERCKSPTSDH 750
751 VNGHCTSPTSQSCSSGKRLSSADVSKVNRWGPGRPPFRKAQSAACMEISL 800
801 PVTTEETRENSYNRSRSSSISSIDKDSKEAITALYFMESFARKNDSTVSP 850
851 CLFVGTSLGMVVLISLNLPSSDEQRFTEPVVVLPSGTFLSLKGAVLTFSC 900
901 MDRTGSLMQPPYEVWRDPNNTDENEKTWKRKLVMNYSSSSQEMGDHQYTI 950
951 ICSEKQAKVFSLPSQTCLYVHNITETSFILQADVVVMCNSACLACFCANG 1000
1001 HIMIMSLPSLRPMLDVNYLPLTDMRIARTFCFTNEGQALYLVSPTEIQRL 1050
1051 TYSQEMCDNIQDMLGDLFTPIETPEAQNRGFLKGLFGGSGQTFDREELFG 1100
1101 EASAGKASRSLAQHIPGPGSIEGMKGAAGGVMGELTRARIALDERGQRLG 1150
1151 ELEEKTAGMMTSAEAFSKHAHELMLKYKDKKWYQF 1185
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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