 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q60592 from www.uniprot.org...
The NucPred score for your sequence is 0.98 (see score help below)
1 MVTGLSPLLFRKLSNPDIFAPTGKVKLQRQLSQDDCKLRRGSLASSLSGK 50
51 QLLPLSSSVHSSVGQVTWQSTGEASNLVRMRNQSLGQSAPSLTAGLKELS 100
101 LPRRGSFCRTSNRKSLIVTSSTSPTLPRPHSPLHGHTGNSPLDSPRNFSP 150
151 NAPAHFSFVPARRTDGRRWSLASLPSSGYGTNTPSSTVSSSCSSQEKLHQ 200
201 LPFQPTADELHFLTKHFSTENVPDEEGRRSPRMRPRSRSLSPGRSPVSFD 250
251 SEIIMMNHVYKERFPKATAQMEERPSLTFISSNTPDSVLPLADGALSFIH 300
301 HQVIEMARDCLDKSRSGLITSHYFYELQENLEKLLQDAHERSESSDVAFV 350
351 IQLVKKLMIIIARPARLLECLEFDPEEFYHLLEAAEGHAKEGHGIKCDIP 400
401 RYIVSQLGLTRDPLEEMAQLSSYDSPDTPETDDSVEGRGVSQPSQKTPSE 450
451 EDFETIKLISNGAYGAVFLVRHKSTRQRFAMKKINKQNLILRNQIQQAFV 500
501 ERDILTFAENPFVVSMFCSFETKRHLCMVMEYVEGGDCATLLKNIGALPV 550
551 DMVRLYFAETVLALEYLHNYGIVHRDLKPDNLLITSMGHIKLTDFGLSKI 600
601 GLMSLTTNLYEGHIEKDAREFLDKQVCGTPEYIAPEVILRQGYGKPVDWW 650
651 AMGIILYEFLVGCVPFFGDTPEELFGQVISDEIVWPEGDDALPPDAQDLT 700
701 SKLLHQNPLERLGTSSAYEVKQHPFFMGLDWTGLLRQKAEFIPQLESEDD 750
751 TSYFDTRSERYHHVDSEDEEEVSEDGCLEIRQFSSCSPRFSKVYSSMERL 800
801 SLLEERRTPPPTKRSLSEEKEDHSDGLAGLKGRDRSWVIGSPEILRKRLS 850
851 VSESSHTESDSSPPMTVRHRCSGLPDGPHCPEETSSTPRKQQQEGIWVLI 900
901 PPSGEGSSRPVPERPLERQLKLDEEPPGQSSRCCPALETRGRGTPQLAEE 950
951 ATAKAISDLAVRRARHRLLSGDSIEKRTTRPVNKVIKSASATALSLLIPS 1000
1001 EHHACSPLASPMSPHSQSSNPSSRDSSPSRDFLPALGSLRPPIIIHRAGK 1050
1051 KYGFTLRAIRVYMGDTDVYTVHHMVWHVEDGGPASEAGLRQGDLITHVNG 1100
1101 EPVHGLVHTEVVELVLKSGNKVSISTTPLENTSIKVGPARKGSYKAKMAR 1150
1151 RSKRSKGKDGQESRKRSSLFRKITKQASLLHTSRSLSSLNRSLSSGESGP 1200
1201 GSPTHSHSLSPRSPPQGYRVAPDAVHSVGGNSSQSSSPSSSVPSSPAGSG 1250
1251 HTRPSSLHGLAPKLQRQYRSPRRKSAGSIPLSPLAHTPSPPATAASPQRS 1300
1301 PSPLSGHGSQSFPTKLHLSPPLGRQLSRPKSAEPPRSPLLKRVQSAEKLA 1350
1351 AALAAAEKKLAPSRKHSLDLPHGELKKELTPREASPLEVVGTRSVLSGKG 1400
1401 PLPGKGVLQPAPSRALGTLRQDRAERRESLQKQEAIREVDSSEDDTDEEP 1450
1451 ENSQATQEPRLSPHPEASHNLLPKGSGEGTEEDTFLHRDLKKQGPVLSGL 1500
1501 VTGATLGSPRVDVPGLSPRKVSRPQAFEEATNPLQVPSLSRSGPTSPTPS 1550
1551 EGCWKAQHLHTQALTALCPSFSELTPTGCSAATSTSGKPGTWSWKFLIEG 1600
1601 PDRASTNKTITRKGEPANSQDTNTTVPNLLKNLSPEEEKPQPPSVPGLTH 1650
1651 PLLEVPSQNWPWESECEQMEKEEPSLSITEVPDSSGDRRQDIPCRAHPLS 1700
1701 PETRPSLLWKSQELGGQQDHQDLALTSDELLKQT 1734
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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