| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P12685 from www.uniprot.org...
The NucPred score for your sequence is 0.98 (see score help below)
1 MHFRRTMSRVPTLASLEIRYKKSFGHKFRDFIALCGHYFAPVKKYIFPSF 50
51 IAVHYFYTISLTLITSILLYPIKNTRYIDTLFLAAGAVTQGGLNTVDINN 100
101 LSLYQQIVLYIVCCISTPIAVHSCLAFVRLYWFERYFDGIRDSSRRNFKM 150
151 RRTKTILERELTARTMTKNRTGTQRTSYPRKQAKTDDFQEKLFSGEMVNR 200
201 DEQDSVHSDQNSHDISRDSSNNNTNHNGSSGSLDDFVKEDETDDNGEYQE 250
251 NNSYSTVGSSSNTVADESLNQKPKPSSLRFDEPHSKQRPARVPSEKFAKR 300
301 RGSRDISPADMYRSIMMLQGKHEATAEDEGPPLVIGSPADGTRYKSNVNK 350
351 LKKATGINGNKIKIRDKGNESNTDQNSVSSEANSTASVSDESSLHTNFGN 400
401 KVPSLRTNTHRSNSGPIAITDNAETDKKHGPSIQFDITKPPRKISKRVST 450
451 FDDLNPKSSVLYRKKASKKYLMKHFPKARRIRQQIKRRLSTGSIEKNSSN 500
501 NVSDRKPITDMDDDDDDDDNDGDNNEEYFADNESGDEDERVQQSEPHSDS 550
551 ELKSHQQQQEKHQLQQNLHRMYKTKSFDDNRSRAVPMERSRTIDMAEAKD 600
601 LNELARTPDFQKMVYQNWKAHHRKKPNFRKRGWNNKIFEHGPYASDSDRN 650
651 YPDNSNTGNSILHYAESILHHDGSHKNGSEEASSDSNENIYSTNGGSDHN 700
701 GLNNYPTYNDDEEGYYGLHFDTDYDLDPRHDLSKGSGKTYLSWQPTIGRN 750
751 SNFLGLTRAQKDELGGVEYRAIKLLCTILVVYYVGWHIVAFVMLVPWIIL 800
801 KKHYSEVVRDDGVSPTWWGFWTAMSAFNDLGLTLTPNSMMSFNKAVYPLI 850
851 VMIWFIIIGNTGFPILLRCIIWIMFKISPDLSQMRESLGFLLDHPRRCFT 900
901 LLFPKAATWWLLLTLAGLNITDWILFIILDFGSTVVKSLSKGYRVLVGLF 950
951 QSVSTRTAGFSVVDLSQLHPSIQVSYMLMMYVSVLPLAISIRRTNVYEEQ 1000
1001 SLGLYGDMGGEPEDTDTEDDGNDEDDDEENESHEGQSSQRSSSNNNNNNN 1050
1051 RKKKKKKKTENPNEISTKSFIGAHLRKQLSFDLWFLFLGLFIICICEGDK 1100
1101 IKDVQEPNFNIFAILFEIVSAYGTVGLSLGYPDTNQSFSRQFTTLSKLVI 1150
1151 IAMLIRGKNRGLPYSLDRAIILPSDRLEHIDHLEGMKLKRQARTNTEDPM 1200
1201 TEHFKRSFTDVKHRWGALKRKTTHSRNPKRSSTTL 1235
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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