 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q05030 from www.uniprot.org...
The NucPred score for your sequence is 0.42 (see score help below)
1 MGLPEVMPASVLRGQLLLFVLLLLGPQISQGLVITPPGPEFVLNISSTFV 50
51 LTCSSSAPVMWEQMSQVPWQEAAMNQDGTFSSVLTLTNVTGGDTGEYFCV 100
101 YNNSLGPELSERKRIYIFVPDPTMGFLPMDSEDLFIFVTDVTETTIPCRV 150
151 TDPQLEVTLHEKKVDIPLHVPYDHQRGFIGTFEDKTYICKTTIGDREVDS 200
201 DTYYVYSLQVSSINVSVNAVQTVVRQGESITIRCIVMGNDVVNFQWTYPR 250
251 MKSGRLVEPVTDYLFGVPSRIGSILHIPTAELSDSGTYTCNVSVSVNDHG 300
301 DEKAINVTVIENGYVRLLETLEDVQIAELHRSRTLQVVFEAYPTPSVLWF 350
351 KDNRTLGDSSAGELVLSTRNVSETRYVSELTLVRVKVSEAGYYTMRAFHA 400
401 DDQVQLSFKLQVNVPVRVLELSESHPANGEQILRCRGRGMPQPNVTWSTC 450
451 RDLKRCPRKLSPTPLGNSSKEESQLETNVTFWEEDQEYEVVSTLRLRHVD 500
501 QPLSVRCMLQNSMGRDSQEVTVVPHSLPFKVVVISAILALVVLTVISLII 550
551 LIMLWQRKPRYEIRWKVIESVSSDGHEYIYVDPVQLPYDSTWELPRDQLV 600
601 LGRTLGSGAFGQVVEATAHGLSHSQATMKVAVKMLKSTARSSEKQALMSE 650
651 LKIMSHLGPHLNVVNLLGACTKGGPIYIITEYCRYGDLVDYLHRNKHTFL 700
701 QRHSNKHCPPSTELYSNALPVGLSLPSHLNLTGESDGGYMDMSKDESVDY 750
751 VPMLDMKGHIKYADIESSSYMAPYDNYVPSAPERTYRATLINDSPVLSYT 800
801 DLVGFSYQVANGMEFLASKNCVHRDLAARNVLICEGKLVKICDFGLARDI 850
851 MRDSNYISKGSTFLPLKWMAPESIFNSLYTTLSDVWSFGILLWEIFTLGG 900
901 TPYPELPMNDQFYNAIKRGYRMAQPAHASDEIYEIMQKCWEEKFETRPPF 950
951 SQLVLLLERLLGEGYKKKYQQVDEEFLRSDHPAILRSQARLPGLHSLRSP 1000
1001 LDTSSVLYTAVQPNETDNDYIIPLPDPKPDAADEGLLEGSPSLASSTLNE 1050
1051 VNTSSTISCDSPLELQEEPQAEPEAQLEQPQDSGCPGPLAEAEDSFL 1097
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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