 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P40434 from www.uniprot.org...
The NucPred score for your sequence is 0.88 (see score help below)
1 MKVSDRRKFEKANFDEFESALNNKNDLVHCPSITLFESIPTEVRSFYEDE 50
51 KSGLIKVVKFRTGAMDRKRSFEKVVISVMVGKNVKKFLTFVEDEPDFQGG 100
101 PIPSKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSLFYLNRGYYNELSF 150
151 RVLERCHEIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAP 200
201 YMFLLLHVDELSIFSAYQASLPGEKKVDTERLKRDLCPRKPIEIKYFSQI 250
251 CNDMMNKKDRLGDILHIILRACALNFGAGPRGGAGDEEDRSITNEEPIIP 300
301 SVDEHGLKVCKLRSPNTPRRLRKTLDAVKALLVSSCACTARDLDIFDDNN 350
351 GVAMWKWIKILYHEVAQETTLKDSYRITLVPSSDGISLLAFAGPQRNVYV 400
401 DDTTRRIQLYTDYNKNGSSEPRLKTLDGLTSDYVFYFVTVLRQMQICALG 450
451 NSYDAFNHDPWMDVVGFEDPNQVTNRDISRIVLYSYMFLNTAKGCLVEYA 500
501 TFRQYMRELPKNAPQKLNFREMRQGLIALGRHCVGSRFETDLYESATSEL 550
551 MANHSVQTGRNIYGVDSFSLTSVSGTTATLLQERASERWIQWLGLESDYH 600
601 CSFSSTRNAEDVVAGEAASSNHHQKISRVTRKRPREPKSTNDILVAGQKL 650
651 FGSSFEFRDLHQLRLCYEIYMADTPSVAVQAPPGYGKTELFHLPLIALAS 700
701 KGDVEYVSFLFVPYTVLLANCMIRLGRCGCLNVAPVRNFIEEGYDGVTDL 750
751 YVGIYDDLASTNFTDRIAAWENIVECTFRTNNVKLGYLIVDEFHNFETEV 800
801 YRQSQFGGITNLDFDAFEKAIFLSGTAPEAVADAALQRIGLTGLAKKSMD 850
851 INELKRSEDLSRGLSSYPTRMFNLIKEKSEVPLGHVHKIRKKVESQPEEA 900
901 LKLLLALFESEPESKAIVVASTTNEVEELACSWRKYFRVVWIHGKLGAAE 950
951 KVSRTKEFVTDGSMQVLIGTKLVTEGIDIKQLMMVIMLDNRLNIIELIQG 1000
1001 VGRLRDGGLCYLLSRKNSWAARNRKGELPPIKEGCITEQVREFYGLESKK 1050
1051 GKKGQHVGCCGSRTDLSADTVELIERMDRLAEKQATASMSIVALPSSFQE 1100
1101 SNSSDRYRKYCSSDEDSNTCIHGSANASTNASTNAITTASTNVRTNATTN 1150
1151 ASTNATTNASTNASTNATTNASTNATTNSSTNATTTASTNVRTSATTTAS 1200
1201 INVRTSATTTESTNSSTNATTTESTNSSTNATTTESTNSNTSATTTASIN 1250
1251 VRTSATTTESTNSSTSATTTASINVRTSATTTKSINSSTNATTTESTNSN 1300
1301 TNATTTESTNSSTNATTTESTNSSTNATTTESTNSNTSAATTESTNSNTS 1350
1351 ATTTESTNASAKEDANKDGNAEDNRFHPVTDINKESYKRKGSQMVLLERK 1400
1401 KLKAQFPNTSENMNVLQFLGFRSDEIKHLFLYGIDIYFCPEGVFTQYGLC 1450
1451 KGCQKMFELCVCWAGQKVSYRRIAWEALAVERMLRNDEEYKEYLEDIEPY 1500
1501 HGDPVGYLKYFSVKRREIYSQIQRNYAWYLAITRRRETISVLDSTRGKQG 1550
1551 SQVFRMSGRQIKELYFKVWSNLRESKTEVLQYFLNWDEKKCQEEWEAKDD 1600
1601 TVVVEALEKGGVFQRLRSMTSAGLQGPQYVKLQFSRHHRQLRSRYELSLG 1650
1651 MHLRDQIALGVTPSKVPHWTAFLSMLIGLFYNKTFRQKLEYLLEQISEVW 1700
1701 LLPHWLDLANVEVLAADDTRVPLYMLMVAVHKELDSDDVPDGRFDILLCR 1750
1751 DSSREVGE 1758
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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