 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q93YU5 from www.uniprot.org...
The NucPred score for your sequence is 0.64 (see score help below)
1 MGIFNGLPVPSDKTYLREELARIDESWAAARFDSLPHVVHILTSKDREAD 50
51 IHILKEQSDVVEEVVDEVVHAYHGGFNKAIQNYSQILRLFSESTEKIGDL 100
101 KHDLAEAKQSLGARNKQLHQLWYRSVTLRHIISLLDQIEGIAKVPSRIEK 150
151 LIADKQFYAAIQVYLQSSLMLEREGLQTVGALQDVRSELTKLRGALFFKI 200
201 LDDLHAHLYNRGEYSSVASSIYERDDEVPTTTAVAASRMSSQPLSRRTRT 250
251 LKGDSQFGVRGLTNGSYRTASNDESSSFDGHDEEDSVEHDESTADTARNG 300
301 TDSKLLSHQLPPWLSDSTPDEFIEAVRKSDDPLHVKYLQTLVQCLCMLGK 350
351 VAAAGAIICQKLRPTIHEIIISKIKAHLETTNLSKSACSQGDRSVAAGLH 400
401 LIKGQSEAYRLSKEKPQNGISNSGTHLAVSPVSPLMAPGGKAQAAAKELL 450
451 DSILDTIVKIFENHVVIGELLEMKASQHDINTPRSLPTDVNWNTESEASQ 500
501 ATGGYTISFPLTVLQSECQQLICEILRATPEAASADAAAQTAKLAKKAPK 550
551 KDKRDAPEDGLTFTFRFTDATVSISNQGADLIRQGWGKRAPNASLEGYGS 600
601 AAVLPEQGIYLAASIYRPVLQFTDKITSMLPKKHSQLVNDGLLTFTENFV 650
651 KDHLLPTMFVDYRKGVQQAISSAAAFRPRAHTTTYTATVEKGRPILQGLL 700
701 AIDLLAKEVLGWAQAMPKFATDLVKYVQTFLERTFERCRTSYMEAVLEKL 750
751 SYMLIGRHDIEKLMRLDAASACLPSTLGHAVSHSEAVGTEVELSDLFLSL 800
801 RPIKQDNLIRDDNKLILLASLSDSLEYVADSIERLGQAVPRVASQAEGNS 850
851 RNQAASPRNLASFADEYRKLATDCLKVLRVEMQLETVFHLQEMTNREYLE 900
901 DEDAEEPDDFVISLTSQITRREEGMAPFISGEKRNYVFGGISGIAANASI 950
951 KALADMRSINLFGVQQICRNTIAVEQAMAAIPYIDGETVQQNLDRVRTYF 1000
1001 ELLNMPFEALLAFIAEHDQMFTPTEYSNLLKVNVPGRDTPSDAQSRLLEI 1050
1051 LSH 1053
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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