 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q98UF7 from www.uniprot.org...
The NucPred score for your sequence is 0.73 (see score help below)
1 MGSQTLQILRQGVWASVTGGWYYDPDQNTFVNALHLYIWLFLLCFPFTLY 50
51 MALQPSMVIVGIYCGVIAAMFLLLKTVNYRLHHALDEGEVVEHQTRESKG 100
101 SRGGTGGANDPVTRREDSNGLGDPGGGIEMADFIRQETPPVDCSSRNSYV 150
151 GMDLNQRMSSTHGRTTVAKAPGSEETVIFRRERSTFRRQAVRRRHNAGSN 200
201 PTPPTSLIGSPLRYALHEADRPSGVRSWYRTVKSQPSRTPSQVTVLSTSA 250
251 SLLARNGSTHLEGSQDKASTVGTTSLQDEFGTLTPSLYEIRGCHIGLGNF 300
301 ESATRRASNNIWDTDSHLSSSTSVRFYPHDLISLHHIRANRLLTMDPELL 350
351 EQQDDLSPDLQDAPLGQDNPSAASAAGKTRQYYRLWLLPFLWVGLHFDRL 400
401 TLLALFDRNREVLENVLAVVLAVLVAFLGSVLLIHGFFADIWVFQFCLVI 450
451 ASCQYSLLKSVQPDSSSPRHGHNRIIAYSRPVYFCLCCGLIWLLHYGSLR 500
501 TTSSRFTLYGVALTSSLVLASARDLVIVFTLCFPIIFFVGLLPQVNTFVM 550
551 YLFEQLDIHVFGGNASTSLLSALYSILRSIVTVALLYCFCYGALKENWEP 600
601 HHIPVLFSVFCGLLVAVSYHLSRQSSDPSVLMYVPLSKVFPQLRSKNPED 650
651 PLSEVQDPLPEKLRASVNERLQSDLIVCVVIAVLYFAIHVSTVFIALQPY 700
701 LSYVLYGLLGAVGLLTHYLLPQLRKQLPWYCFSHPLLKTKEYYQFEVRDA 750
751 AHVMWFEKFHVWLLFVEKNVLYPLVILNELSGSARELASPKRLDTEVGAL 800
801 MITVAGLKLLRSSYSSPTYQYITILFTVLFFTLDHRHLSETLLLDLFLMS 850
851 IIFSKMWELFYKLHFVYTYIAPWQITWGSAFHAFAQPFAVPHSAMLFVQA 900
901 VVSSIFSTPLNPFLGSAIFITSYVRPVKFWERDYNTKRVDHSNTRLASQL 950
951 DRNPGSDDNNLNSIFYEHLTRSLQHSLCGDLLLGRWGNFSTGDCFILASD 1000
1001 YLNALVHLIEIGNGLVTFQLRGLEFRGTYCQQREVEAITEGVEEDEGCCC 1050
1051 CEPGHLPHILSFNAAFGQRWLAWEVVVTKYVLEGYSITDNSAASMLQVFE 1100
1101 LRRILTTYYVKGIIYYVIASPKLEEWLANDTMKEGLRGCSERNYVDLDAT 1150
1151 FNPNIDEDYDHRLSGISRDSFCGVYLGWIQYCNSRRTKPLDSEKDSALVL 1200
1201 LCFGLCVLGRRALGTAAHQMSSNLESFLYGLHALFKGDFRISSVRDEWIF 1250
1251 ADMELLRKVVVPGIRMSLKLHQDHFTSPDEYDEPAVLFEAISTHQQNLVI 1300
1301 AHEGDPAWRSAVLSNAPSLLALRHVLDEGTNEYKIIMLNRRYLSFRVIKV 1350
1351 NKECVRGLWAGQQQELVFLRNRNPERGSIQNAKQALRNMINSSCDQPIGY 1400
1401 PIYVSPLTTSYCNSHPQLRHILGGPISFGNIRNFVVSTWHRLRKGCGAGC 1450
1451 NSGGNIEDSDAGGLSCGTSQSSQSVQSGLVRHSPARASVVSQSSSYRYSS 1500
1501 SRHSSLRTSTTGLEPCRRSSTSQLSLRTLPTSLQLRLGSTSDPAGPSSSL 1550
1551 SSHSIPPCKRHTLVGLLGNDGLCSTVTDPLSQHHHPHHHPQQHNPTHATV 1600
1601 RRDDISYRVQIVDVGQVLENINLSKRKELQWPDDAMRHKAGRTCWRDWSP 1650
1651 LEGMEGHVIHRWVPCSRDPGSRSHIDKTILLVQVEDKIVPIIETGVIELG 1700
1701 AEV 1703
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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