 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P60283 from www.uniprot.org...
The NucPred score for your sequence is 0.90 (see score help below)
1 MKKIITLSAPPPSQFSFLSEFQFSLPELRQIQFKSYYYFIYKNLISELNI 50
51 FPEIFDLNQEFQFELLNKEYKLIKPEKTTIKFHYNTYSSDLYVTCRLLRR 100
101 KKKIEIQKQTIFIGSIPLIDYQSTFRINSVTRVIINQILRSPGIYYNSEL 150
151 DHNGISIYTGTIISDWGGRLKLEIDSKTRIWARISKKRKVSILVLLLAMG 200
201 LTIKQILDSVCSSKIFLDFLKEKKKKKEHLQSTEDAMVELYKQLYYIGGD 250
251 LLFSESIRKELQKKFFQQRCELGKIGRLNVNKKLSLDIPENEFFLLPQDI 300
301 LAAIDYLIKIKFGIGTLDDIDHLKNRRIRSVADLLQDQLKLALIRLENSV 350
351 RQVMRRTTKRKRLLSPKNLITQTPLIATFKEFFGSHPLSQFLDQTNSLAE 400
401 IVHKRRLSSLGPGGVTRRTAGFQVRDIHFSHYTRICPIETSEGMNAGLIA 450
451 SLAIHANVNNWGFLESPFYKISKNVKEEKIINLSAGEDEYYRIATGNCLA 500
501 LDQGTQKIQITPARYRQEFLAIAWEQIHLRSIYPLQYFSVGVSLIPFLEH 550
551 NDANRALMGSNMQRQAVPLIKLEKCIVGTGLESQVALDSGNVMITKQSEK 600
601 IMYTDGKKISLLNNTNETVNTHLIIYQRSNNSTCIHQKPQVISKKFLKKG 650
651 QVLTDGAAILKGELTLGKNILVAYMPWEGYNFEDAILISERLIYEDIYTS 700
701 IHIERYEIESRNTNQGPEKITKEIPHLENSVLRHLDKNGLVIPGSWVETG 750
751 DVLVGKLTPQETEESLRAPEGKLLQAIFGIQVTNAKETCLKVPLNGKGRV 800
801 IDVIWISKKENSSNYEKIIHVYIAQKRKIQVGDKVAGRHGNKGIISKILP 850
851 RQDMPYLQDGTPIDMVLSPLGVPSRMNVGQIFECLLGLAGYFLGKHYRIT 900
901 PFDEKYEREASRKLVFSELYKASKKTGNLWLFEPENPGKSRLLNGRTGEI 950
951 FEQAVTVGKAYMLKLIHQVDDKIHARSSGPYALVTQQPLRGRSRRGGQRV 1000
1001 GEMEVWALEGFGVAYILQEMLTIKSDHIHARYEVLGAIITGEPIPKPKTA 1050
1051 PESFLLLVRELRSLSLELDHAVIFEKNLNIKFKDV 1085
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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