 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P38798 from www.uniprot.org...
The NucPred score for your sequence is 0.82 (see score help below)
1 MDDGRKKELHDLNTRAWNGEEVFPLKSKKLDSSIKRNTGFIKKLKKGFVK 50
51 GSESSLLKDLSEASLEKYLSEIIVTVTECLLNVLNKNDDVIAAVEIISGL 100
101 HQRFNGRFTSPLLGAFLQAFENPSVDIESERDELQRITRVKGNLRVFTEL 150
151 YLVGVFRTLDDIESKDAIPNFLQKKTGRKDPLLFSILREILNYKFKLGFT 200
201 TTIATAFIKKFAPLFRDDDNSWDDLIYDSKLKGALQSLFKNFIDATFARA 250
251 TELHKKVNKLQREHQKCQIRTGKLRDEYVEEYDKLLPIFIRFKTSAITLG 300
301 EFFKLEIPELEGASNDDLKETASPMITNQILPPNQRLWENEDTRKFYEIL 350
351 PDISKTVEESQSSKTEKDSNVNSKNINLFFTDLEMADCKDIIDDLSNRYW 400
401 SSYLDNKATRNRILKFFMETQDWSKLPVYSRFIATNSKYMPEIVSEFINY 450
451 LDNGFRSQLHSNKINVKNIIFFSEMIKFQLIPSFMIFHKIRTLIMYMQVP 500
501 NNVEILTVLLEHSGKFLLNKPEYKELMEKMVQLIKDKKNDRQLNMNMKSA 550
551 LENIITLLYPPSVKSLNVTVKTITPEQQFYRILIRSELSSLDFKHIVKLV 600
601 RKAHWDDVAIQKVLFSLFSKPHKISYQNIPLLTKVLGGLYSYRRDFVIRC 650
651 IDQVLENIERGLEINDYGQNMHRISNVRYLTEIFNFEMIKSDVLLDTIYH 700
701 IIRFGHINNQPNPFYLNYSDPPDNYFRIQLVTTILLNINRTPAAFTKKCK 750
751 LLLRFFEYYTFIKEQPLPKETEFRVSSTFKKYENIFGNTKFERSENLVES 800
801 ASRLESLLKSLNAIKSKDDRVKGSSASIHNGKESAVPIESITEDDEDEDD 850
851 ENDDGVDLLGEDEDAEISTPNTESAPGKHQAKQDESEDEDDEDDDEDDDD 900
901 DDDDDDDDGEEGDEDDDEDDDDEDDDDEEEEDSDSDLEYGGDLDADRDIE 950
951 MKRMYEEYERKLKDEEERKAEEELERQFQKMMQESIDARKSEKVVASKIP 1000
1001 VISKPVSVQKPLLLKKSEEPSSSKETYEELSKPKKIAFTFLTKSGKKTQS 1050
1051 RILQLPTDVKFVSDVLEEEEKLKTERNKIKKIVLKRSFD 1089
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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