 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9JIB6 from www.uniprot.org...
The NucPred score for your sequence is 0.55 (see score help below)
1 MAEHGESSEDRISEIDYEFLAELSARFGMNLVQLAKSQEEEDHKERMKMK 50
51 KGFNSQMRSEAKRLKTFESYDTFRSWTPQEMAAAGFYHTGVKLGVQCFCC 100
101 SLILFGNSLRKLPIERHKKLRPECEFLQGKDVGNIGKYDIRVKSPEKMLR 150
151 GGKARYHEEEARLESFEDWPFYAHGTSPRALSAAGFVFTGKRDTVQCFSC 200
201 GGSLGNWEEGDDPWKEHAKWFPKCEFLQSKKSSEEIAQYIQDYEGFVHVT 250
251 GEHFVKSWVRRELPMVSAYCNDSVFTNEELRMDMFKDWPQESPVGFEALV 300
301 RAGFFYTGKKDIVRCFSCGGCLEKWAEGDDPMEDHIKFFPECVFLQTLKS 350
351 SAEVIPTLQSQYALPEATETTRESNHDDAAAVHSTVVDLGRSEAQWFQEA 400
401 RSLSEQLRDTYTKTSFCHMNLPEVCSSLGTDHLLGCDVSIISKHVSQPVQ 450
451 GALTIPEVFSNLSSVMCVEGEAGSGKTTFLKRIAFLWASGCCPLLYRFQL 500
501 VFYLSLSSITPDQGLANIICTQLLGAGGCISEVCLSSSIQQLQHQVLFLL 550
551 DDYSGLASLPQALHTLITKNYLFRTCLLIAVHTNRVRDIRPYLGTSLEIQ 600
601 EFPFYNTVFVLRKFFSHDIICVEKLIIYFSENKDLQGVYKTPLFVAAVCN 650
651 DWNQNASAQDDFQDVTLFHSYMQYLSLKYKATAESLQATVSSCGQLALTG 700
701 LFSSCFEFNSDDLAEAGVDEDVKLTTFLMSKFTAQRLRPVYRFLGPLFQE 750
751 FLAAVRLTELLSSDRQEDQDLGLYYLRQIDSPLKAINSFNIFLYYVSSHS 800
801 SSKAAPTVVSHLLQLVDEKESLENMSENEDYMKLHPQTFLWFQFVRGLWL 850
851 VSPESFSSFVSEHLLRLALIFAYESNTVAECSPFILQFLRGRTLALRVLN 900
901 LEYFWDHPESLLLLRSLKVSINGNKMSSYVDYSFKTYFENLQPPAINEEY 950
951 TSAFEHVSEWRRNFAQDEEIIKNYENIWPRALPDISEGYWNLSPKPCKIP 1000
1001 KLEVQVNNMGPADQALLQVLMEVFSASQSIEFHLFNSSGFLESIRPALEL 1050
1051 SKASVTKCSMSRLELSRAEQELLLTLPALQSLEVSETNQLPDQLFHNLHK 1100
1101 FLGLKELCVRLDGKPDVLSVLPEEFLNLHHMEKLSIRTSTESDLSKLVKF 1150
1151 IQNFPNLHVFHLKCDFLSNCESLMTALASCKKLREIEFSGQCFEAMTFVN 1200
1201 ILPNFVSLKILSLKGQQFADKETSEKFAQALGSLRNLEELLVPTGDGIHQ 1250
1251 VAKLIVRQCLQLPCLRVLAFHDILDDESVIEIARAATSGSFQKLENLDIS 1300
1301 MNHKITEEGYRNFFQALDNLPNLQMLNICRNIPGRIQVQATTVKALGHCV 1350
1351 SRLPSLTRLGMLSWLLDEEDMKVINDVKERHPQSKRLTIFWKWIVPFSPV 1400
1401 VLE 1403
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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