 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P18709 from www.uniprot.org...
The NucPred score for your sequence is 0.91 (see score help below)
1 MKGIVLALLLALAGSERTHIEPVFSESKISVYNYEAVILNGFPESGLSRA 50
51 GIKINCKVEISAYAQRSYFLKIQSPEIKEYNGVWPKDPFTRSSKLTQALA 100
101 EQLTKPARFEYSNGRVGDIFVADDVSDTVANIYRGILNLLQVTIKKSQDV 150
151 YDLQESSVGGICHTRYVIQEDKRGDQIRIIKSTDFNNCQDKVSKTIGLEL 200
201 AEFCHSCKQLNRVIQGAATYTYKLKGRDQGTVIMEVTARQVLQVTPFAER 250
251 HGAATMESRQVLAWVGSKSGQLTPPQIQLKNRGNLHYQFASELHQMPIHL 300
301 MKTKSPEAQAVEVLQHLVQDTQQHIREDAPAKFLQLVQLLRASNFENLQA 350
351 LWKQFAQRTQYRRCLLDALPMAGTVDCLKFIKQLIHNEELTTQEAAVLIT 400
401 FAMRSARPGQRNFQISADLVQDSKVQKYSTVHKAAILAYGTMVRRYCDQL 450
451 SSCPEHALEPLHELAAEAANKGHYEDIALALKALGNAGQPESIKRIQKFL 500
501 PGFSSSADQLPVRIQTDAVMALRNIAKEDPRKVQEILLQIFMDRDVRTEV 550
551 RMMACLALFETRPGLATVTAIANVAARESKTNLQLASFTFSQMKALSKSS 600
601 VPHLEPLAAACSVALKILNPSLDNLGYRYSKVMRVDTFKYNLMAGAAAKV 650
651 FIMNSANTMFPVFILAKFREYTSLVENDDIEIGIRGEGIEEFLRKQNIQF 700
701 ANFPMRKKISQIVKSLLGFKGLPSQVPLISGYIKLFGQEIAFTELNKEVI 750
751 QNTIQALNQPAERHTMIRNVLNKLLNGVVGQYARRWMTWEYRHIIPTTVG 800
801 LPAELSLYQSAIVHAAVNSDVKVKPTPSGDFSAAQLLESQIQLNGEVKPS 850
851 VLVHTVATMGINSPLFQAGIEFHGKVHAHLPAKFTAFLDMKDRNFKIETP 900
901 PFQQENHLVEIRAQTFAFTRNIADLDSARKTLVVPRNNEQNILKKHFETT 950
951 GRTSAEGASMMEDSSEMGPKKYSAEPGHHQYAPNINSYDACTKFSKAGVH 1000
1001 LCIQCKTHNAASRRNTIFYQAVGEHDFKLTMKPAHTEGAIEKLQLEITAG 1050
1051 PKAASKIMGLVEVEGTEGEPMDETAVTKRLKMILGIDESRKDTNETALYR 1100
1101 SKQKKKNKIHNRRLDAEVVEARKQQSSLSSSSSSSSSSSSSSSSSSSSSS 1150
1151 SSSPSSSSSSSYSKRSKRREHNPHHQRESSSSSSQEQNKKRNLQENRKHG 1200
1201 QKGMSSSSSSSSSSSSSSSSSSSSSSSSSSSSEENRPHKNRQHDNKQAKM 1250
1251 QSNQHQQKKNKFSESSSSSSSSSSSEMWNKKKHHRNFYDLNFRRTARTKG 1300
1301 TEHRGSRLSSSSESSSSSSESAYRHKAKFLGDKEPPVLVVTFKAVRNDNT 1350
1351 KQGYQMVVYQEYHSSKQQIQAYVMDISKTRWAACFDAVVVNPHEAQASLK 1400
1401 WGQNCQDYKINMKAETGNFGNQPALRVTANWPKIPSKWKSTGKVVGEYVP 1450
1451 GAMYMMGFQGEYKRNSQRQVKLVFALSSPRTCDVVIRIPRLTVYYRALRL 1500
1501 PVPIPVGHHAKENVLQTPTWNIFAEAPKLIMDSIQGECKVAQDQITTFNG 1550
1551 VDLASALPENCYNVLAQDCSPEMKFMVLMRNSKESPNHKDINVKLGEYDI 1600
1601 DMYYSADAFKMKINNLEVSEEHLPYKSFNYPTVEIKKKGNGVSLSASEYG 1650
1651 IDSLDYDGLTFKFRPTIWMKGKTCGICGHNDDESEKELQMPDGSVAKDQM 1700
1701 RFIHSWILPAESCSEGCNLKHTLVKLEKAIATDGAKAKCYSVQPVLRCAK 1750
1751 GCSPVKTVEVSTGFHCLPSDVSLDLPEGQIRLEKSEDFSEKVEAHTACSC 1800
1801 ETSPCAA 1807
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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