 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O95466 from www.uniprot.org...
The NucPred score for your sequence is 0.84 (see score help below)
1 MGNAAGSAEQPAGPAAPPPKQPAPPKQPMPAAGELEERFNRALNCMNLPP 50
51 DKVQLLSQYDNEKKWELICDQERFQVKNPPAAYIQKLKSYVDTGGVSRKV 100
101 AADWMSNLGFKRRVQESTQVLRELETSLRTNHIGWVQEFLNEENRGLDVL 150
151 LEYLAFAQCSVTYDMESTDNGASNSEKNKPLEQSVEDLSKGPPSSVPKSR 200
201 HLTIKLTPAHSRKALRNSRIVSQKDDVHVCIMCLRAIMNYQSGFSLVMNH 250
251 PACVNEIALSLNNKNPRTKALVLELLAAVCLVRGGHDIILAAFDNFKEVC 300
301 GEQHRFEKLMEYFRNEDSNIDFMVACMQFINIVVHSVENMNFRVFLQYEF 350
351 THLGLDLYLERLRLTESDKLQVQIQAYLDNIFDVGALLEDTETKNAVLEH 400
401 MEELQEQVALLTERLRDAENESMAKIAELEKQLSQARKELETLRERFSES 450
451 TAMGPSRRPPEPEKAPPAAPTRPSALELKVEELEEKGLIRILRGPGDAVS 500
501 IEILPVAVATPSGGDAPTPGVPTGSPSPDLAPAAEPAPGAAPPPPPPLPG 550
551 LPSPQEAPPSAPPQAPPLPGSPEPPPAPPLPGDLPPPPPPPPPPPGTDGP 600
601 VPPPPPPPPPPPGGPPDALGRRDSELGPGVKAKKPIQTKFRMPLLNWVAL 650
651 KPSQITGTVFTELNDEKVLQELDMSDFEEQFKTKSQGPSLDLSALKSKAA 700
701 QKAPSKATLIEANRAKNLAITLRKGNLGAERICQAIEAYDLQALGLDFLE 750
751 LLMRFLPTEYERSLITRFEREQRPMEELSEEDRFMLCFSRIPRLPERMTT 800
801 LTFLGNFPDTAQLLMPQLNAIIAASMSIKSSDKLRQILEIVLAFGNYMNS 850
851 SKRGAAYGFRLQSLDALLEMKSTDRKQTLLHYLVKVIAEKYPQLTGFHSD 900
901 LHFLDKAGSVSLDSVLADVRSLQRGLELTQREFVRQDDCMVLKEFLRANS 950
951 PTMDKLLADSKTAQEAFESVVEYFGENPKTTSPGLFFSLFSRFIKAYKKA 1000
1001 EQEVEQWKKEAAAQEAGADTPGKGEPPAPKSPPKARRPQMDLISELKRRQ 1050
1051 QKEPLIYESDRDGAIEDIITVIKTVPFTARTGKRTSRLLCEASLGEEMPL 1100
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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