 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q968X7 from www.uniprot.org...
The NucPred score for your sequence is 0.30 (see score help below)
1 MGEKEIVDGCVAACHIAYACSEVAFTYPITPSSTISEVADSWMSRGRRNI 50
51 FDQVVSVVEMQSEMGSAGALHGSLSVGCSTTTFTASQGLLLMIPNMYKIA 100
101 GELWPCVFHVTARAIATSSLSIFGDHNDIMAARQTGWAFLGAMTVQEVMD 150
151 LALVSHVSTFECSVPFVNFFDGFRTSHELQKIDMISYETIKKIFPYEKLK 200
201 EFRERALNPTHPTLRGTATSSDVYFQLAEARNKYYESTPDIVQSVMDRLA 250
251 KLIGRSYHLFDYYGHPDAEFLIVVMGSGGLTIEEMIDYLMEKSNEKVGMI 300
301 KVRLFRPWSIDAFVKKIPKTTKRITVLERCKESGSLGEPLCLDVSTSIMR 350
351 SELSSNNILVLGGRYGLASKEFTPGMALAVWENMISENPINNFSVGIDDD 400
401 VTFKSLFVRQPRLDLLTSETKQCLFWGLGSDGTVSANKNAIKIIGESTDL 450
451 QVQGYFAYDAKKAGGATMSHLRFGPKPIKSAYLLQRCDYVAVHHPSYVHK 500
501 FDVLENIKQGGCFVLNCPWSTLEELNHELPSKIKHQIASRDVKFYVIDAQ 550
551 RIAQESNLGRRINNILMVVFFSLTNIIPLDLAIKLVKEAIKKTYGKKGDA 600
601 VVNSNWKAVDLTLESLIQISYDKSQWISKDKCGEKSLPATAVETGNKDQE 650
651 ITKSTVLKQKPEHDVNQFVKDILGPVNALKGDELPVSMFEPTGTVPLGTT 700
701 AYEKRGIAMSIPIVDMNKCTQCNYCSIVCPHAAIRPFLLDEAEFKNAPET 750
751 MHIPKAKGGQEFSSYYYRIQVTPLDCTGCELCVHACPDDALHMEGLQKME 800
801 AVEKTHWDYLIGLPNKAEKFDRTTVKGSQFQQPLLEFSAACEGCGETPYV 850
851 KLLTQLFGERMVIANATGCSSIWGASYPSVPYTKNQKGYGPAWGNSLFED 900
901 NAEYGLGMVVGYRQRRDRFRELVSNEILKDITEEEEFLKDDNASVQGRNE 950
951 IITKYDHLKDYLRSWLKNIRNGEACQSLFEEISKLLEDNLINSNNFAQVL 1000
1001 KKDRIELLEKLYDSRDLIPKISHWIVGGDGWAYDIGYAGLDHVLSFGEDV 1050
1051 NIIILDTEVYSNTGGQASKSTPFGAIAKFAQSGNLRQKKDIGSIAMEYGS 1100
1101 VYVASVALGANYSQTIKSLLEAEKYPGTSLIVAYSTCIEHGYTKYNLQQE 1150
1151 SVKLAVESGYWPLYRYNPELVRTEVVDNLTTIVSSGFTLDSKKVKVDIEN 1200
1201 FLKRENRFLQLIRSNPELASMAKDKLKAHSDKRFQKMKDMSENVTVTALK 1250
1251 DQIKKLKDQLISIQNASKTGELAASGLINADLFIEQEMHVLYGTETGNSE 1300
1301 EVAQYIQSQLVSRGYSSSSLNLDDLDIDEFLNPDKFSTVIIVTSTSGQGE 1350
1351 FPGSSGILYEALLKKHLENQDDKFCSFMRFGIFGLGDSNYVFFNEAAKKW 1400
1401 DKLLLDCGAVRIGAVGMGDDQSEEKYETELIEWLPDYLQLINAPEPKHDE 1450
1451 KSEIPKATTFKVTILDSCRNDILNESTGTLCEKLDENNNIGNSHYKPIIP 1500
1501 PNSVLLPVIENKRITNQDYDKDVRHIVFKLIGDGGDTPSLSYCLGDSLAL 1550
1551 YGQNPVNEAIKAIEMFGYNPYSLLRLSINEENEANNTNKVNQRYSSLFGY 1600
1601 DITVLQLFVECLDLWGKPNRKFFQEFYRYCSNPEEKIQAKKWAQNEGKKL 1650
1651 IEEFSSKTGTYLDVFKMFESARPTLAQLLDIVPFIKSRSYSIASCNKFVN 1700
1701 GEKIELCVGIVDWKLESGEIRYGQCTGFLNRLPILDSESKIDSIPRLPSN 1750
1751 IKASAFNLPFDYRSPVIMACMGTGIAPFRAFVQNKKYIRDVLKEEIGPVI 1800
1801 LYFGCRYYDNDYLYREELENYVKEGVITSLNIAFSRDPKGYKTSNCENIR 1850
1851 YAQKMYVQHLMLENSQEIYENMIEKCGYFYLCGTKQVPIDIRKAIIQIII 1900
1901 KHSSTTEQVTSEEDANSILNSIQIMGRYNVEAWS 1934
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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