| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P36044 from www.uniprot.org...
The NucPred score for your sequence is 0.98 (see score help below)
1 MLQRISSKLHRRFLSGLLRVKHYPLRRILLPLILLQIIIITFIWSNSPQR 50
51 NGLGRDADYLLPNYNELDSDDDSWYSILTSSFKNDRKIQFAKTLYENLKF 100
101 GTNPKWVNEYTLQNDLLSVKMGPRKGSKLESVDELKFYDFDPRLTWSVVL 150
151 NHLQNNDADQPEKLPFSWYDWTTFHELNKLISIDKTVLPCNFLFQSAFDK 200
201 ESLEAIETELGEPLFLYERPKYAQKLWYKAARNQDRIKDSKELKKHCSKL 250
251 FTPDGHGSPKGLRFNTQFQIKELYDKVRPEVYQLQARNYILTTQSHPLSI 300
301 SIIESDNSTYQVPLQTEKSKNLVQSGLLQEYINDNINSTNKRKKNKQDVE 350
351 FNHNRLFQEFVNNDQVNSLYKLEIEETDKFTFDKDLVYLSPSDFKFDASK 400
401 KIEELEEQKKLYPDKFSAHNENYLNSLKNSVKTSPALQRKFFYEAGAVKQ 450
451 YKGMGFHRDKRFFNVDTLINDKQEYQARLNSMIRTFQKFTKANGIISWLS 500
501 HGTLYGYLYNGMAFPWDNDFDLQMPIKHLQLLSQYFNQSLILEDPRQGNG 550
551 RYFLDVSDSLTVRINGNGKNNIDARFIDVDTGLYIDITGLASTSAPSRDY 600
601 LNSYIEERLQEEHLDINNIPESNGETATLPDKVDDGLVNMATLNITELRD 650
651 YITSDENKNHKRVPTDTDLKDLLKKELEELPKSKTIENKLNPKQRYFLNE 700
701 KLKLYNCRNNHFNSFEELSPLINTVFHGVPALIPHRHTYCLHNEYHVPDR 750
751 YAFDAYKNTAYLPEFRFWFDYDGLKKCSNINSWYPNIPSINSWNPNLLKE 800
801 ISSTKFESKLFDSNKVSEYSFKNLSMDDVRLIYKNIPKAGFIEVFTNLYN 850
851 SFNVTAYRQKELEIQYCQNLTFIEKKKLLHQLRINVAPKLSSPAKDPFLF 900
901 GYEKAMWKDLSKSMNQTTLDQVTKIVHEEYVGKIIDLSESLKYRNFSLFN 950
951 ITFDETGTTLDDNTEDYTPANTVEVNPVDFKSNLNFSSNSFLDLNSYGLD 1000
1001 LFAPTLSDVNRKGIQMFDKDPIIVYEDYAYAKLLEERKRREKKKKEEEEK 1050
1051 KKKEEEEKKKKEEEEKKKKEEEEKKKKEEEEKKKKEEEEKKKQEEEEKKK 1100
1101 KEEEEKKKQEEGEKMKNEDEENKKNEDEEKKKNEEEEKKKQEEKNKKNED 1150
1151 EEKKKQEEEEKKKNEEEEKKKQEEGHSN 1178
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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