 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P51828 from www.uniprot.org...
The NucPred score for your sequence is 0.22 (see score help below)
1 MPAKGRYFLNEGEEGPDQDALYEKYQLTSQHGPLLLTLLLVAATACVALI 50
51 IIAFSQGDPSRHQAILGMAFLVLAVFAALSVLMYVECLLRRWLRALALLT 100
101 WACLVALGYVLVFDAWTKAACAWEQVPFFLFIVFVVYTLLPFSMRGAVAV 150
151 GAVSTASHLLVLGSLMGGFTTPSVRVGLQLLANAVIFLCGNLTGAFHKHQ 200
201 MQDASRDLFTYTVKCIQIRRKLRIEKRQQENLLLSVLPAHISMGMKLAII 250
251 ERLKEHGDRRCMPDNNFHSLYVKRHQNVSILYADIVGFTQLASDCSPKEL 300
301 VVVLNELFGKFDQIAKANECMRIKILGDCYYCVSGLPVSLPTHARNCVKM 350
351 GLDMCQAIKQVREATGVDINMRVGIHSGNVLCGVIGLRKWQYDVWSHDVS 400
401 LANRMEAAGVPGRVHITEATLKHLDKAYEVEDGHGQQRDPYLKEMNIRTY 450
451 LVIDPRSQQPPPPSQHLPRPKGDAALKMRASVRMTRYLESWGAARPFAHL 500
501 NHRESVSSGETHVPNGRRPKSVPQRHRRTPDRSMSPKGRSEDDSYDDEML 550
551 SAIEGLSSTRPCCSKSDDFYTFGSIFLEKGFEREYRLAPIPRARHDFACA 600
601 SLIFVCILLVHVLLMPRTAALGVSFGLVACVLGLVLGLCFATKFSRCCPA 650
651 RGTLCTISERVETQPLLRLTLAVLTIGSLLTVAIINLPLMPFQVPELPVG 700
701 NETGLLAASSKTRALCEPLPYYTCSCVLGFIACSVFLRMSLEPKVVLLTV 750
751 ALVAYLVLFNLSPCWQWDCCGQGLGNLTKPNGTTSGTPSCSWKDLKTMTN 800
801 FYLVLFYITLLTLSRQIDYYCRLDCLWKKKFKKEHEEFETMENVNRLLLE 850
851 NVLPAHVAAHFIGDKLNEDWYHQSYDCVCVMFASVPDFKVFYTECDVNKE 900
901 GLECLRLLNEIIADFDELLLKPKFSGVEKIKTIGSTYMAAAGLSVASGHE 950
951 NQELERQHAHIGVMVEFSIALMSKLDGINRHSFNSFRLRVGINHGPVIAG 1000
1001 VIGARKPQYDIWGNTVNVASRMESTGELGKIQVTEETCTILQGLGYSCEC 1050
1051 RGLINVKGKGELRTYFVCTDTAKFQGLGLN 1080
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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