 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P13217 from www.uniprot.org...
The NucPred score for your sequence is 0.65 (see score help below)
1 MTKKYEFDWIIPVPPELTTGCVFDRWFENEKETKENDFERDALFKVDEYG 50
51 FFLYWKSEGRDGDVIELCQVSDIRAGGTPKDPKILDKVTKKNGTNIPELD 100
101 KRSLTICSNTDYINITYHHVICPDAATAKSWQKNLRLITHNNRATNVCPR 150
151 VNLMKHWMRLSYCVEKSGKIPVKTLAKTFASGKTEKLVYTCIKDAGLPDD 200
201 KNATMTKEQFTFDKFYALYHKVCPRNDIEELFTSITKGKQDFISLEQFIQ 250
251 FMNDKQRDPRMNEILYPLYEEKRCTEIINDYELDEEKKKNVQMSLDGFKR 300
301 YLMSDENAPVFLDRLDFYMEMDQPLAHYYINSSHNTYLSGRQIGGKSSVE 350
351 MYRQTLLAGCRCVELDCWNGKGEDEEPIVTHGHAYCTEILFKDCIQAIAD 400
401 CAFVSSEYPVILSFENHCNRAQQYKLAKYCDDFFGDLLLKEPLPDHPLDP 450
451 GLPLPPPCKLKRKILIKNKRMKPEVEKVELELWLKGELKTDDDPEEDASA 500
501 GKPPEAAAAPAPAPEAAAAAEGAAEGGGGAEAEAAAANYSGSTTNVHPWL 550
551 SSMVNYAQPIKFQGFDKAIEKNIAHNMSSFAESAGMNYLKQSSIDFVNYN 600
601 KRQMSRIYPKGTRADSSNYMPQVFWNAGCQMVSLNFQSSDLPMQLNQGKF 650
651 EYNGGCGYLLKPDFMRRADKDFDPFADAPVDGVIAAQCSVKVIAGQFLSD 700
701 KKVGTYVEVDMFGLPSDTVKKEFRTRLVANNGLNPVYNEDPFVFRKVVLP 750
751 DLAVLRFGVYEESGKILGQRILPLDGLQAGYRHVSLRTEANFPMSLPMLF 800
801 VNIELKIYVPDGFEDFMAMLSDPRGFAGAAKQQNEQMKALGIEEQSGGAA 850
851 RDAGKAKEEEKKEPPLVFEPVTLESLRQEKGFQKVGKKQIKELDTLRKKH 900
901 AKERTSVQKTQNAAIDKLIKGKSKDDIRNDANIKNSINDQTKQWTDMIAR 950
951 HRKEEWDMLRQHVQDSQDAMKALMLTVQAAQIKQLEDRHARDIKDLNAKQ 1000
1001 AKMSADTAKEVQNDKTLKTKNEKDRRLREKRQNNVKRFMEEKKQIGVKQG 1050
1051 RAMEKLKLAHSKQIEEFSTDVQKLMDMYKIEEEAYKTQGKTEFYA 1095
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.) |
Go back to the NucPred Home Page.