 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q61IS6 from www.uniprot.org...
The NucPred score for your sequence is 0.85 (see score help below)
1 MLSILHSLSWMAHWINPTATIAPSTPPQAGEKNANVKNGTVQTNGVNHTE 50
51 RLAGRAPNLLHPAIDYPGITSYEAGGSLILTDIFPTVLFMFVVLFCRWFN 100
101 GFAPRQERFQRLEYEAILRRRRFRVQSEESEELEDHEAYSETDICTQLIA 150
151 SSANVACNINVDLVNQNRFYFFVKQNNEDETAVPSDVPPPETSIKNEDTE 200
201 VNLVFASAEDNGYISSTFEVSETSLMVTSEVYEVEKVSVNEDQSSRPVNV 250
251 IVNESDDEQSLRSQDGSRCSDEAMNSCMSASEDEDVESQEDSYHVNDATE 300
301 DSVSSIKTQEDEPIEEELASCHSDEDDHQNEVLGDEEASKYDNLPVEMRS 350
351 AKEGDESEGTIDSSVSSSTSSTPDDDEDDSATSYDSDDIEIQMFEYDLGT 400
401 VCASASISIPRPSIIPKKNKKAEVNANEERMDDVSVSPGRSDSPGGGGGH 450
451 SDSFQDPLDPGEQLGSDDEEQEDPRDYKRGGYHPVNIGDVFNSRYHVIRK 500
501 LGWGHFSTVWLAWDTQEKRFTAMKIVKSAEHYTEAALDEIKLLLSVRGAD 550
551 PEDTGCHKVVQLLDEFTVTGINGQHVAMVFEVLGCNLLKLIIRSNYRGLH 600
601 LEQVRKICKQILEALRYMHEKCGIIHTDIKPENVLITMSREEIKIMAQHA 650
651 VVARKMNMKMSGSAVSTAPDHLVKMAQENMTKNKKKKMKKKAKKQREKLE 700
701 AELAGLEGLKMDANGLQEAYNNAPQNGIRMRPPSLLFNGPIPQLLQGSSC 750
751 VNTPSSPRSVPPPPALYPQAGGVCNQTYHLSQVILNEQVELESFNTSQVE 800
801 DVNIEDAVNGNGNGTNNKIELKSPDRFDRTTLTPFSDPESKIGELASPSS 850
851 EFLSSPMSMLPPGGVLPAPPVGPNIADPYCDIDVKIADLGNACWVNHHYT 900
901 DDIQTRQYRALEVLIGSGYGPPADIWSTACMAFELATGDYLFEPHQGDNY 950
951 SRDEDHLAHISELLGQISPSIYKKGKHWREFFHKNGNLLHIHNLKPWSLY 1000
1001 EVLRQKYEWSHEDAQQFESFLRPMLDFDQEKRATANDALKHPFLLPFGGK 1050
1051 APRDPEVLQRLYPDGQVPEALDGNQEVYRDENDSNSASERSANRSAGSDD 1100
1101 EEEFHMDRPGPSGVINEPADVSEIESFQLNLQ 1132
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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