 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6P1C6 from www.uniprot.org...
The NucPred score for your sequence is 0.63 (see score help below)
1 MGAPGLRAATAALGLLLCAGLGRAGPAGSGGHGAPGQLLDDDAQRPCPAA 50
51 CHCLGDLLDCSRRRLVRLPDPLPAWVTRLDLSHNRLSFIQTSSLSHLQSL 100
101 QEVKLNNNELETIPNLGSISANIRQLSLAGNAIDKILPEQLEAFQSLETL 150
151 DLSNNNISELRTAFPPLQLKYLYINNNRVSSMEPGYFDNLASTLLVLKLN 200
201 RNRISAIPPKMFKLPQLQHLELNRNKIKNVDGLTFQGLGALKSLKMQRNG 250
251 VTKLMDGAFWGLSNMEVLQLDHNNLTEITKGWLYGLLMLRELHLSQNAIN 300
301 RISPDAWEFCQKLSELDLTFNHLSRLDDSSFLGLSLLNALHIGNNKVSYI 350
351 ADCAFRGLTSLKTLDLRNNEISWTIEDMSGAFSGLDRLRQLILQGNRIRS 400
401 ITKKAFAGLDTLEHLDLSGNAIMSLQSNAFSQMKKLQQLHLNTSSLLCDC 450
451 QLRWLPQWVAENNFQSFVNASCAHPQLLKGRSIFTVSPDGFVCDDFPKPQ 500
501 ITVQPETQSAIKGSDVSFTCSAASSSDSPMTFAWKKDNEALQDAEMENYA 550
551 HLRAQGGELMEYTTILRLRNVEFTSEGKYQCVISNHFGSSYSVKAKLTIN 600
601 MLPSFTKTPMDLTIRAGAMARLECAAVGHPAPQIAWQKDGGTDFPAARER 650
651 RMHVMPEDDVFFIVDVKIEDIGVYSCTAQNSAGSVSANATLTVLETPSFL 700
701 RPLLDRTVTKGETAVLQCIAGGSPPPRLNWTKDDSPLVVTERHFFAAGNQ 750
751 LLIIVDSDVSDAGKYTCEMSNTLGTERGNVRLSVIPTPTCDSPHMTAPSL 800
801 DGDGWATVGVVIIAVVCCVVGTSLVWVVIIYHTRRRNEDCSITNTDETNL 850
851 PADIPSYLSSQGTLADRQDGYISSESGSHHQFVTSSGGGFFLPQHDGAGT 900
901 CHFDDSSEADVEAASDPFLCPFVGSTGPVYLQGNLYSPDPFEVYLPGCSS 950
951 DPRTALMDHCESSYVKQDRFSCARPSEEPCERSLKSIPWPHSRKLTDSTY 1000
1001 PPNEGHTVQTLCLNKSSVDFSTGPEPGSATSSNSFMGTFGKPLRRPHLDA 1050
1051 FSSSAQPPDCQPRPCHGKSLSSPELDSESEENDKERTDFREENHRCTYQQ 1100
1101 IFHTYRTPDCQPCDSDT 1117
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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