| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O13433 from www.uniprot.org...
The NucPred score for your sequence is 0.94 (see score help below)
1 MLESLNRRNSIDSNQADNDNDNDNHSNDELSPSELYYSPSGSPPKSQLLL 50
51 RKSSSPSSYSPIKSDLPNIYSHLRSNDSESPPQPSPKQQSSLSSSSSSSS 100
101 SSNTKSSTTKNIFKKLLRINKSSDNIDESRSIVSNNGGSPMSDSTTVTST 150
151 LSTDTAPKRGKSIQRSQILHHTDSDSLYLENQIELRPEISKSIGNIKIPS 200
201 IFTNDGMPLLKISHKSKKRILFWIDPSCFKFSWRMANSTTTTTSATTSAT 250
251 TSGLPQGITNTTALSNSAIISTPAIATSAIHRLSITNRTTHEFVLDDIKS 300
301 IYIQNEGSGYREELNISQKLEKNWITIIYFNHKKNSLKSLHLITDNDHDF 350
351 KKLISAIYNLKQLRSQLAKEFLIDLNELDENYVKMLLNKELLAGDNGNVD 400
401 GNEVDIRKSHKHVREFLSFNDILKYSKRLNINVNTNHLQQIFDQVLLLSS 450
451 ATTEKPVSTPLFEKGLNFEQFKQFVSILKDRKDLQEIWDSLAQGKEVLQF 500
501 DEIKNFIINIQKENFSDDDDNSTINLIFQKYCSNDNGWNKESLNEYLLSS 550
551 YSTPYREITQTQTNYYDYPLNEYFISSSHNTYLTGRQVAGDSSVEGYIRT 600
601 LQRGCRCVEIDIWNGDSNTTTTTVIGTKDDDDKNEYEPIVNHGRTFTKPI 650
651 SFANVIRAIKKFAFIVSPWPLILSLEIHCSPECQIKVVNILKDILGENMI 700
701 IAPIDIDSVILPSPAELKHKFIIKVKKTTSFQNLIETENGSFTTSTTTTT 750
751 TTTTTTTTATSLSEDNENNKSNSSSTSSFIIRRRKNKSPKIINELSNLGI 800
801 YTQGIKFRNFSLPESKTFNHCFSLGEKSINRMIKDDDKKISLDKHNRRYL 850
851 MRVYPSGTRLKSSNFNPLPYWSHGVQMVATNWQTYDLGQQLNEALFENKI 900
901 FQGYVLKPSVLRKPTLKSSSSNVDTRTSLTTTNSKTIRFNFEIISGHQLP 950
951 KFPKDDYKDQAINPYISFEIIGAQDVQWDNNDSSPIAPTTSSSPFIRTTK 1000
1001 IIRENGFNPNFNTKFSGSIITTTNDLIFIKFVVYASTSLNYPDYGENFPI 1050
1051 AILVTKLNYLKQGYRYIYLNDLLGEQLVYSSIFIKIEYDEDLLNEFINK 1099
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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