 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9BZZ2 from www.uniprot.org...
The NucPred score for your sequence is 0.36 (see score help below)
1 MGFLPKLLLLASFFPAGQASWGVSSPQDVQGVKGSCLLIPCIFSFPADVE 50
51 VPDGITAIWYYDYSGQRQVVSHSADPKLVEARFRGRTEFMGNPEHRVCNL 100
101 LLKDLQPEDSGSYNFRFEISEVNRWSDVKGTLVTVTEEPRVPTIASPVEL 150
151 LEGTEVDFNCSTPYVCLQEQVRLQWQGQDPARSVTFNSQKFEPTGVGHLE 200
201 TLHMAMSWQDHGRILRCQLSVANHRAQSEIHLQVKYAPKGVKILLSPSGR 250
251 NILPGELVTLTCQVNSSYPAVSSIKWLKDGVRLQTKTGVLHLPQAAWSDA 300
301 GVYTCQAENGVGSLVSPPISLHIFMAEVQVSPAGPILENQTVTLVCNTPN 350
351 EAPSDLRYSWYKNHVLLEDAHSHTLRLHLATRADTGFYFCEVQNVHGSER 400
401 SGPVSVVVNHPPLTPVLTAFLETQAGLVGILHCSVVSEPLATLVLSHGGH 450
451 ILASTSGDSDHSPRFSGTSGPNSLRLEIRDLEETDSGEYKCSATNSLGNA 500
501 TSTLDFHANAARLLISPAAEVVEGQAVTLSCRSGLSPTPDARFSWYLNGA 550
551 LLHEGPGSSLLLPAASSTDAGSYHCRARDGHSASGPSSPAVLTVLYPPRQ 600
601 PTFTTRLDLDAAGAGAGRRGLLLCRVDSDPPARLQLLHKDRVVATSLPSG 650
651 GGCSTCGGCSPRMKVTKAPNLLRVEIHNPLLEEEGLYLCEASNALGNAST 700
701 SATFNGQATVLAIAPSHTLQEGTEANLTCNVSREAAGSPANFSWFRNGVL 750
751 WAQGPLETVTLLPVARTDAALYACRILTEAGAQLSTPVLLSVLYPPDRPK 800
801 LSALLDMGQGHMALFICTVDSRPLALLALFHGEHLLATSLGPQVPSHGRF 850
851 QAKAEANSLKLEVRELGLGDSGSYRCEATNVLGSSNTSLFFQVRGAWVQV 900
901 SPSPELQEGQAVVLSCQVHTGVPEGTSYRWYRDGQPLQESTSATLRFAAI 950
951 TLTQAGAYHCQAQAPGSATTSLAAPISLHVSYAPRHVTLTTLMDTGPGRL 1000
1001 GLLLCRVDSDPPAQLRLLHGDRLVASTLQGVGGPEGSSPRLHVAVAPNTL 1050
1051 RLEIHGAMLEDEGVYICEASNTLGQASASADFDAQAVNVQVWPGATVREG 1100
1101 QLVNLTCLVWTTHPAQLTYTWYQDGQQRLDAHSIPLPNVTVRDATSYRCG 1150
1151 VGPPGRAPRLSRPITLDVLYAPRNLRLTYLLESHGGQLALVLCTVDSRPP 1200
1201 AQLALSHAGRLLASSTAASVPNTLRLELRGPQPRDEGFYSCSARSPLGQA 1250
1251 NTSLELRLEGVRVILAPEAAVPEGAPITVTCADPAAHAPTLYTWYHNGRW 1300
1301 LQEGPAASLSFLVATRAHAGAYSCQAQDAQGTRSSRPAALQVLYAPQDAV 1350
1351 LSSFRDSRARSMAVIQCTVDSEPPAELALSHDGKVLATSSGVHSLASGTG 1400
1401 HVQVARNALRLQVQDVPAGDDTYVCTAQNLLGSISTIGRLQVEGARVVAE 1450
1451 PGLDVPEGAALNLSCRLLGGPGPVGNSTFAWFWNDRRLHAEPVPTLAFTH 1500
1501 VARAQAGMYHCLAELPTGAAASAPVMLRVLYPPKTPTMMVFVEPEGGLRG 1550
1551 ILDCRVDSEPLASLTLHLGSRLVASSQPQGAPAEPHIHVLASPNALRVDI 1600
1601 EALRPSDQGEYICSASNVLGSASTSTYFGVRALHRLHQFQQLLWVLGLLV 1650
1651 GLLLLLLGLGACYTWRRRRVCKQSMGENSVEMAFQKETTQLIDPDAATCE 1700
1701 TSTCAPPLG 1709
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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