 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q7RTU9 from www.uniprot.org...
The NucPred score for your sequence is 0.48 (see score help below)
1 MALSLWPLLLLLLLLLLLSFAVTLAPTGPHSLDPGLSFLKSLLSTLDQAP 50
51 QGSLSRSRFFTFLANISSSFEPGRMGEGPVGEPPPLQPPALRLHDFLVTL 100
101 RGSPDWEPMLGLLGDMLALLGQEQTPRDFLVHQAGVLGGLVEVLLGALVP 150
151 GGPPTPTRPPCTRDGPSDCVLAADWLPSLLLLLEGTRWQALVQVQPSVDP 200
201 TNATGLDGREAAPHFLQGLLGLLTPTGELGSKEALWGGLLRTVGAPLYAA 250
251 FQEGLLRVTHSLQDEVFSILGQPEPDTNGQCQGGNLQQLLLWGVRHNLSW 300
301 DVQALGFLSGSPPPPPALLHCLSTGVPLPRASQPSAHISPRQRRAITVEA 350
351 LCENHLGPAPPYSISNFSIHLLCQHTKPATPQPHPSTTAICQTAVWYAVS 400
401 WAPGAQGWLQACHDQFPDEFLDAICSNLSFSALSGSNRRLVKRLCAGLLP 450
451 PPTSCPEGLPPVPLTPDIFWGCFLENETLWAERLCGEASLQAVPPSNQAW 500
501 VQHVCQGPTPDVTASPPCHIGPCGERCPDGGSFLVMVCANDTMYEVLVPF 550
551 WPWLAGQCRISRGGNDTCFLEGLLGPLLPSLPPLGPSPLCLTPGPFLLGM 600
601 LSQLPRCQSSVPALAHPTRLHYLLRLLTFLLGPGAGGAEAQGMLGRALLL 650
651 SSLPDNCSFWDAFRPEGRRSVLRTIGEYLEQDEEQPTPSGFEPTVNPSSG 700
701 ISKMELLACFSPVLWDLLQREKSVWALQILVQAYLHMPPENLQQLVLSAE 750
751 REAAQGFLTLMLQGKLQGKLQVPPSEEQALGRLTALLLQRYPRLTSQLFI 800
801 DLSPLIPFLAVSDLMRFPPSLLANDSVLAAIRDYSPGMRPEQKEALAKRL 850
851 LAPELFGEVPAWPQELLWAVLPLLPHLPLENFLQLSPHQIQALEDSWPAA 900
901 GLGPGHARHVLRSLVNQSVQDGEEQVRRLGPLACFLSPEELQSLVPLSDP 950
951 TGPVERGLLECAANGTLSPEGRVAYELLGVLRSSGGAVLSPRELRVWAPL 1000
1001 FSQLGLRFLQELSEPQLRAMLPVLQGTSVTPAQAVLLLGRLLPRHDLSLE 1050
1051 ELCSLHLLLPGLSPQTLQAIPRRVLVGACSCLAPELSRLSACQTAALLQT 1100
1101 FRVKDGVKNMGTTGAGPAVCIPGQPIPTTWPDCLLPLLPLKLLQLDSLAL 1150
1151 LANRRRYWELPWSEQQAQFLWKKMQVPTNLTLRNLQALGTLAGGMSCEFL 1200
1201 QQINSMVDFLEVVHMIYQLPTRVRGSLRACIWAELQRRMAMPEPEWTTVG 1250
1251 PELNGLDSKLLLDLPIQLMDRLSNESIMLVVELVQRAPEQLLALTPLHQA 1300
1301 ALAERALQNLAPKETPVSGEVLETLGPLVGFLGTESTRQIPLQILLSHLS 1350
1351 QLQGFCLGETFATELGWLLLQESVLGKPELWSQDEVEQAGRLVFTLSTEA 1400
1401 ISLIPREALGPETLERLLEKQQSWEQSRVGQLCREPQLAAKKAALVAGVV 1450
1451 RPAAEDLPEPVPNCADVRGTFPAAWSATQIAEMELSDFEDCLTLFAGDPG 1500
1501 LGPEELRAAMGKAKQLWGPPRGFRPEQILQLGRLLIGLGDRELQELILVD 1550
1551 WGVLSTLGQIDGWSTTQLRIVVSSFLRQSGRHVSHLDFVHLTALGYTLCG 1600
1601 LRPEELQHISSWEFSQAALFLGTLHLQCSEEQLEVLAHLLVLPGGFGPIS 1650
1651 NWGPEIFTEIGTIAAGIPDLALSALLRGQIQGVTPLAISVIPPPKFAVVF 1700
1701 SPIQLSSLTSAQAVAVTPEQMAFLSPEQRRAVAWAQHEGKESPEQQGRST 1750
1751 AWGLQDWSRPSWSLVLTISFLGHLL 1775
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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