 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q99247 from www.uniprot.org...
The NucPred score for your sequence is 0.90 (see score help below)
1 MNQLTVSYGLISPDYCTSQDAHILPITKILYPDIPGKNYFLTSGRDGSII 50
51 LHKNTQLSNEPETAATTIKNDAIRMQVHSDWASDLIHVNMKNSDPSAGDT 100
101 FISVSHDFSIVLISVNAQLTTWDKKIIGDHDDYIKCIVPIHYEMSNDYEL 150
151 EEQEGGPDNVHDGINNGIVVDEQNNFLFVTGGLDRKIKLWCLSSGPEKMA 200
201 TLLHTFDNAQSNDTGSIYSMSPIIPKYSFDDNQTSRPFDFVAGDCNGDLI 250
251 FYSCKYRKEVIRIQNAHRTNIKVVRTLDDSTRLISTSSDGVINVWDLNCR 300
301 HDQTTGALQLPKKIGSWSWDSSIWCVQGTSLDKLYFGDSQGNVMRANLSS 350
351 YEDAKLTRIFKPDHHHHHHHHHEHEEQNISTTDAKVKKYGGILDIALLPN 400
401 EKLLFSFCTDSNLNVLDLTNNHFSVNEGGFALTRSSLLTNRRHVITENTK 450
451 GQMQRWDIVSCELLNTFDSSEGSFDDIVMKYTSKEILSHWCTVSVKVGML 500
501 FVKINPKFLKTEVYGSALKDYQVVNNIEINSDERYNLGKIVINSLFNEFI 550
551 SYEVQKDKLLRKKIFSLKKKDLTNSLTLDTGYNSESKKNNKDKKRKSTFK 600
601 ISSTLSIGNTNSSGTPPNSAPATPVMAETIVLEEQPLLQSASDKAIDDSL 650
651 ELVQPLPASKKPYFRTQSSGSLLSRKFKSFRSTSGRATTGLNTPEEPKGI 700
701 LPDTPHVINDDSAFPQAINTTQQSKDATPESMLWNHPFKLEQKLSAISSQ 750
751 DLPSNNTHNKLRSSENSRANSTSTLEGNEKKKPEFMPDLLEQIQESYKQQ 800
801 YMNTSSLKYLTKRLPVTKIIKASSCPIIRVKSATLVLVHLWKEGSCGGRV 850
851 LFSTLLPPSHVDNETVSGGKENSKPPDDEEVDLQAVDDDKLGKYDLIDGE 900
901 LGSRLNRRQIFEQLEENLPYWFAKALFRDIKTVEEQPKLNFLIMPWSSVG 950
951 GSEAAGNENKKKFISASDTTESSGNDSSDSSLGNGNEAVSPSTQQQFHNM 1000
1001 LKFGRPKTSEQELNPTDLPRISEANVKLVAPGMIRVKKIKLYVADRFETK 1050
1051 TPEMKAKMEPSLWLDLLCRGQVLDNDMTLNTVRTLYWKSQGDIVLEYRRK 1100
1101 VHNSPLVHEVNGNEGK 1116
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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