 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q64739 from www.uniprot.org...
The NucPred score for your sequence is 0.39 (see score help below)
1 MERCSRCHRLLLFLPLVLGLSAAPGWAGAPSVDVLRALRFPSLPDGVRRS 50
51 KGVCPGDVAYRVARPAQLSAPTRQLFPGGFPKDFSLLTVVRTRPGLQAPL 100
101 LTLYSAQGVQQLGLELGRPVRFLYEDQRGRPQASAQPIFRGLSLADGKWH 150
151 HVAVAVKGQSVTLIVDCKKRVTRPLPRSVHPVLDTHGVVIFGAHILDDEV 200
201 FEGDVQELLVVPGVQAAYQSCGQKDLECEREQRDGPQTQKPHRAQRSPKK 250
251 EPARLHKPQSQEPQKQPTESLYYDYEPPYYDVMTTGTAPDYQYPTPGEEE 300
301 GVLESSPLPFLEEEQTDLQVSPTADSFQAEEYGEGGTDSPAGFYDYTYGY 350
351 GDDYREETELGPALSAETAHSGAVAHGPRGLKGEKGEPAVLEPGMFVEGP 400
401 PGPEGPAGLAGPPGIQGNPGPVGDPGERGPPGRAGLPGSDGPPGPPGTSL 450
451 MLPFRFGSSGGDKGPVVAAQEAQAQAILQQARLALRGPPGPMGYTGRPGP 500
501 LGQPGSPGLKGESGDLGPQGPRGPQGLTGPPGKAGRRGRAGADGARGMPG 550
551 EPGMKGDRGFDGLPGLPGEKGQRGDTGAQGLPGPPGEDGERGDDGEIGPR 600
601 GLPGESGPRGLLGPKGPPGIPGPPGVRGMDGPHGPKGSLGPQGEPGPPGQ 650
651 QGTPGAQGLPGPQGAIGPHGEKGARGKPGLPGMPGSDGLPGHPGKEGPPG 700
701 TKGNQGPSGPQGPLGYPGPRGVKGVDGIRGLKGHKGEKGEDGFPGFKGDI 750
751 GVKGDRGEVGVPGSRGEDGPEGPKGRTGPTGDPGPTGLMGEKGKLGVPGL 800
801 PGYPGRQGPKGSLGFPGFPGASGEKGARGLSGKSGPRGERGPTGPRGQRG 850
851 PRGATGKSGAKGTSGGDGPHGPPGERGLPGPQGPNGFPGPKGPPGPAGKD 900
901 GLPGHPGQRGEVGFQGKTGPPGPPGVVGPQGTAGESGPMGERGHSGPPGP 950
951 PGEQGLPGTSGKEGTKGDPGPPGAPGKDGPAGLRGFPGERGLPGTAGGPG 1000
1001 LKGNEGPAGPPGPAGSPGERGAAGSGGPIGPPGRPGPQGPPGAAGEKGVP 1050
1051 GEKGPIGPTGRDGVQGPVGLPGPAGPPGVAGEDGDKGEVGDPGQKGTKGN 1100
1101 KGEHGPPGPPGPIGPVGQPGAAGADGEPGARGPQGHFGAKGDEGTRGFNG 1150
1151 PPGPIGLQGLPGPSGEKGETGDGGPMGPPGPPGPRGPAGPNGADGPQGSP 1200
1201 GGVGNLGPPGEKGEPGESGSPGVQGEPGVKGPRGERGEKGESGQAGEAGP 1250
1251 PGPKGPTGDNGPKGNPGPVGFPGDPGPPGEAGPRGQDGAKGDRGEDGEPG 1300
1301 QPGSPGPTGENGPPGPLGKRGPAGTPGPEGRQGEKGAKGDPGAVGAPGKT 1350
1351 GPVGPAGLAGKPGPDGLRGLPGSVGQQGRPGATGQAGPPGPVGPPGLPGL 1400
1401 RGDAGAKGEKGHPGLIGLIGPTGEQGEKGDRGLPGPQGSPGQKGETGIPG 1450
1451 ASGPIGPGGPPGLPGPSGPKGAKGATGPAGPKGEKGVQGPPGHPGPPGEV 1500
1501 IQPLPIQMPKKTRRSVDGSKLIQDEEAVPTGGAPGSPAGLEEIFGSLDSL 1550
1551 REEIEQMRRPAGTQDSPARTCQDLKLCHPELPDGEYWVDPNQGCARDAFR 1600
1601 VFCNFTAGGETCVTPRDDVTQFSYVDSEGSPVGVVQLTFLRLLSVSAHQD 1650
1651 VSYPCSGVSQDGPLKLRGANEDELSPETSPYVKEFRDGCQTQQGRTVLEV 1700
1701 RTPVLEQLPVLDASFADLGAPTRRGGVLLGPVCFMG 1736
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.) |
Go back to the NucPred Home Page.