 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O88444 from www.uniprot.org...
The NucPred score for your sequence is 0.28 (see score help below)
1 MAGAPRGQGGGGGAGEPGGAERAAGPGGRRGFRACGEEFACPELEALFRG 50
51 YTLRLEQAATLKALAVLSLLAGALALAELLGAPGPAPGLAKGSHPVHCIL 100
101 FLALFVVTNVRSLQVSQLQQVGQLALFFSLTFALLCCPFALGGPARSSAG 150
151 GAMGSTVAEQGVWQLLLVTFVSYALLPVRSLLAIGFGLVVAASHLLVTAA 200
201 LVPAKRPRLWRTLGANALLFFGVNMYGVFVRILTERSQRKAFLQARNCIE 250
251 DRLRLEDENEKQERLLMSLLPRNVAMEMKEDFLKPPERIFHKIYIQRHDN 300
301 VSILFADIVGFTGLASQCTAQELVKLLNELFGKFDELATENHCRRIKILG 350
351 DCYYCVSGLTQPKTDHAHCCVEMGLDMIDTITSVAEATEVDLNMRVGLHT 400
401 GRVLCGVLGLRKWQYDVWSNDVTLANVMEAAGLPGKVHITKTTLACLNGD 450
451 YEVEPGHGHERNTFLRTHNIETFFIVPSHRRKIFPGLILSDIKPAKRMKF 500
501 KTVCYLLVQLMHCRKMFKAEIPFSNVMTCEDDDKRRALRTASEKLRNRSS 550
551 FSTNVVYTTPGTRVNRYISRLLEARQTELEMADLNFFTLKYKHVEREQKY 600
601 HQLQDEYFTSAVVLALILAALFGLIYLLVIPQSVAVLLLLVFSICFLVAC 650
651 TLYLHITRVQCFPGCLTIQIRTALCVFIVVLIYSVAQGCVVGCLPWAWSS 700
701 QSNSSLVVLAAGGRRTVLPALPCESAHHALLCCLVGTLPLAIFLRVSSLP 750
751 KMILLSGLTTSYILVLELSGYTKVGGGALSGRSYEPIMAILLFSCTLALH 800
801 ARQVDVRLRLDYLWAAQAEEERDDMERVKLDNKRILFNLLPAHVAQHFLM 850
851 SNPRNMDLYYQSYSQVGVMFASIPNFNDFYIELDGNNMGVECLRLLNEII 900
901 ADFDELMDKDFYKDLEKIKTIGSTYMAAVGLAPTAGTRAKKSISSHLCTL 950
951 ADFAIDMFDVLDEINYQSYNDFVLRVGINVGPVVAGVIGARRPQYDIWGN 1000
1001 TVNVASRMDSTGVQGRIQVTEEVHRLLKRCSYQFVCRGKVSVKGKGEMLT 1050
1051 YFLEGRTDGNSSHGRTFRLERRMCPYGRGGGQARRPPLCPAAGPPVRPGL 1100
1101 PPAPTSQYLSSTAAGKEA 1118
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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