 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P84634 from www.uniprot.org...
The NucPred score for your sequence is 0.62 (see score help below)
1 MRDEVDLSLTIPSKLLGKRDREQKNCEEEKNKNKKAKKQQKDPILLHTSA 50
51 ATHKFLPPPLTMPYSEIGDDLRSLDFDHADVSSDLHLTSSSSVSSFSSSS 100
101 SSLFSAAGTDDPSPKMEKDPRKIARRYQVELCKKATEENVIVYLGTGCGK 150
151 THIAVMLIYELGHLVLSPKKSVCIFLAPTVALVEQQAKVIADSVNFKVAI 200
201 HCGGKRIVKSHSEWEREIAANEVLVMTPQILLHNLQHCFIKMECISLLIF 250
251 DECHHAQQQSNHPYAEIMKVFYKSESLQRPRIFGMTASPVVGKGSFQSEN 300
301 LSKSINSLENLLNAKVYSVESNVQLDGFVSSPLVKVYYYRSALSDASQST 350
351 IRYENMLEDIKQRCLASLKLLIDTHQTQTLLSMKRLLKRSHDNLIYTLLN 400
401 LGLWGAIQAAKIQLNSDHNVQDEPVGKNPKSKICDTYLSMAAEALSSGVA 450
451 KDENASDLLSLAALKEPLFSRKLVQLIKILSVFRLEPHMKCIIFVNRIVT 500
501 ARTLSCILNNLELLRSWKSDFLVGLSSGLKSMSRRSMETILKRFQSKELN 550
551 LLVATKVGEEGLDIQTCCLVIRYDLPETVTSFIQSRGRARMPQSEYAFLV 600
601 DSGNEKEMDLIENFKVNEDRMNLEITYRSSEETCPRLDEELYKVHETGAC 650
651 ISGGSSISLLYKYCSRLPHDEFFQPKPEFQFKPVDEFGGTICRITLPANA 700
701 PISEIESSLLPSTEAAKKDACLKAVHELHNLGVLNDFLLPDSKDEIEDEL 750
751 SDDEFDFDNIKGEGCSRGDLYEMRVPVLFKQKWDPSTSCVNLHSYYIMFV 800
801 PHPADRIYKKFGFFMKSPLPVEAETMDIDLHLAHQRSVSVKIFPSGVTEF 850
851 DNDEIRLAELFQEIALKVLFERGELIPDFVPLELQDSSRTSKSTFYLLLP 900
901 LCLHDGESVISVDWVTIRNCLSSPIFKTPSVLVEDIFPPSGSHLKLANGC 950
951 WNIDDVKNSLVFTTYSKQFYFVADICHGRNGFSPVKESSTKSHVESIYKL 1000
1001 YGVELKHPAQPLLRVKPLCHVRNLLHNRMQTNLEPQELDEYFIEIPPELS 1050
1051 HLKIKGLSKDIGSSLSLLPSIMHRMENLLVAIELKHVLSASIPEIAEVSG 1100
1101 HRVLEALTTEKCHERLSLERLEVLGDAFLKFAVSRHLFLHHDSLDEGELT 1150
1151 RRRSNVVNNSNLCRLAIKKNLQVYIRDQALDPTQFFAFGHPCRVTCDEVA 1200
1201 SKEVHSLNRDLGILESNTGEIRCSKGHHWLYKKTIADVVEALVGAFLVDS 1250
1251 GFKGAVKFLKWIGVNVDFESLQVQDACIASRRYLPLTTRNNLETLENQLD 1300
1301 YKFLHKGLLVQAFIHPSYNRHGGGCYQRLEFLGDAVLDYLMTSYFFTVFP 1350
1351 KLKPGQLTDLRSLSVNNEALANVAVSFSLKRFLFCESIYLHEVIEDYTNF 1400
1401 LASSPLASGQSEGPRCPKVLGDLVESCLGALFLDCGFNLNHVWTMMLSFL 1450
1451 DPVKNLSNLQISPIKELIELCQSYKWDREISATKKDGAFTVELKVTKNGC 1500
1501 CLTVSATGRNKREGTKKAAQLMITNLKAHENITTSHPLEDVLKNGIRNEA 1550
1551 KLIGYNEDPIDVVDLVGLDVENLNILETFGGNSERSSSYVIRRGLPQAPS 1600
1601 KTEDRLPQKAIIKAGGPSSKTAKSLLHETCVANCWKPPHFECCEEEGPGH 1650
1651 LKSFVYKVILEVEDAPNMTLECYGEARATKKGAAEHAAQAAIWCLKHSGF 1700
1701 LC 1702
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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