 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q92545 from www.uniprot.org...
The NucPred score for your sequence is 0.71 (see score help below)
1 MGKRAGGGATGATTAAVSTSAGAGLEPAAARSGGPRSAAAGLLGALHLVM 50
51 TLVVAAARAEKEAFVQSESIIEVLRFDDGGLLQTETTLGLSSYQQKSISL 100
101 YRGNCRPIRFEPPMLDFHEQPVGMPKMEKVYLHNPSSEETITLVSISATT 150
151 SHFHASFFQNRKILPGGNTSFDVVFLARVVGNVENTLFINTSNHGVFTYQ 200
201 VFGVGVPNPYRLRPFLGARVPVNSSFSPIINIHNPHSEPLQVVEMYSSGG 250
251 DLHLELPTGQQGGTRKLWEIPPYETKGVMRASFSSREADNHTAFIRIKTN 300
301 ASDSTEFIILPVEVEVTTAPGIYSSTEMLDFGTLRTQDLPKVLNLHLLNS 350
351 GTKDVPITSVRPTPQNDAITVHFKPITLKASESKYTKVASISFDASKAKK 400
401 PSQFSGKITVKAKEKSYSKLEIPYQAEVLDGYLGFDHAATLFHIRDSPAD 450
451 PVERPIYLTNTFSFAILIHDVLLPEEAKTMFKVHNFSKPVLILPNESGYI 500
501 FTLLFMPSTSSMHIDNNILLITNASKFHLPVRVYTGFLDYFVLPPKIEER 550
551 FIDFGVLSATEASNILFAIINSNPIELAIKSWHIIGDGLSIELVAVERGN 600
601 RTTIISSLPEFEKSSLSDQSSVTLASGYFAVFRVKLTAKKLEGIHDGAIQ 650
651 ITTDYEILTIPVKAVIAVGSLTCFPKHVVLPPSFPGKIVHQSLNIMNSFS 700
701 QKVKIQQIRSLSEDVRFYYKRLRGNKEDLEPGKKSKIANIYFDPGLQCGD 750
751 HCYVGLPFLSKSEPKVQPGVAMQEDMWDADWDLHQSLFKGWTGIKENSGH 800
801 RLSAIFEVNTDLQKNIISKITAELSWPSILSSPRHLKFPLTNTNCSSEEE 850
851 ITLENPADVPVYVQFIPLALYSNPSVFVDKLVSRFNLSKVAKIDLRTLEF 900
901 QVFRNSAHPLQSSTGFMEGLSRHLILNLILKPGEKKSVKVKFTPVHNRTV 950
951 SSLIIVRNNLTVMDAVMVQGQGTTENLRVAGKLPGPGSSLRFKITEALLK 1000
1001 DCTDSLKLREPNFTLKRTFKVENTGQLQIHIETIEISGYSCEGYGFKVVN 1050
1051 CQEFTLSANASRDIIILFTPDFTASRVIRELKFITTSGSEFVFILNASLP 1100
1101 YHMLATCAEALPRPNWELALYIIISGIMSALFLLVIGTAYLEAQGIWEPF 1150
1151 RRRLSFEASNPPFDVGRPFDLRRIVGISSEGNLNTLSCDPGHSRGFCGAG 1200
1201 GSSSRPSAGSHKQCGPSVHPHSSHSNRNSADVENVRAKNSSSTSSRTSAQ 1250
1251 AASSQSANKTSPLVLDSNTVTQGHTAGRKSKGAKQSQHGSQHHAHSPLEQ 1300
1301 HPQPPLPPPVPQPQEPQPERLSPAPLAHPSHPERASSARHSSEDSDITSL 1350
1351 IEAMDKDFDHHDSPALEVFTEQPPSPLPKSKGKGKPLQRKVKPPKKQEEK 1400
1401 EKKGKGKPQEDELKDSLADDDSSSTTTETSNPDTEPLLKEDTEKQKGKQA 1450
1451 MPEKHESEMSQVKQKSKKLLNIKKEIPTDVKPSSLELPYTPPLESKQRRN 1500
1501 LPSKIPLPTAMTSGSKSRNAQKTKGTSKLVDNRPPALAKFLPNSQELGNT 1550
1551 SSSEGEKDSPPPEWDSVPVHKPGSSTDSLYKLSLQTLNADIFLKQRQTSP 1600
1601 TPASPSPPAAPCPFVARGSYSSIVNSSSSSDPKIKQPNGSKHKLTKAASL 1650
1651 PGKNGNPTFAAVTAGYDKSPGGNGFAKVSSNKTGFSSSLGISHAPVDSDG 1700
1701 SDSSGLWSPVSNPSSPDFTPLNSFSAFGNSFNLTGEVFSKLGLSRSCNQA 1750
1751 SQRSWNEFNSGPSYLWESPATDPSPSWPASSGSPTHTATSVLGNTSGLWS 1800
1801 TTPFSSSIWSSNLSSALPFTTPANTLASIGLMGTENSPAPHAPSTSSPAD 1850
1851 DLGQTYNPWRIWSPTIGRRSSDPWSNSHFPHEN 1883
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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