 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O60014 from www.uniprot.org...
The NucPred score for your sequence is 0.93 (see score help below)
1 MINDTDPESFLRQHVGRTLGCIHSRPEFKDIKGSAERAVMDKELKSFIYG 50
51 YYYYMISDSGRLLPHMFTATNEREFPKNVDQAMEIKLSSKPWYKIDENGG 100
101 HSKFNHAGRICGAKFRVGEPIYRCKECSFDDTCVLCVNCFNPKDHVGHHV 150
151 YTSICTEFNNGICDCGDKEAWNHELNCKGAEDNGRLEDEFDDHDGKISKM 200
201 LESVLIELFDHFIDVFNQNIEPLTTIQKPLIAKLRYFIQNGKYNEQADML 250
251 RRLAYRNQYMDEEESQQQTPSTSLDPLSTLKDYAILVYNDEFHNYSQASA 300
301 AIRQGGPDNKHIDLLTAKIDSEGRSLLRCSADIASLMGGFFSVQSNGLSC 350
351 TITQWYEYLHQEACKYSIMWINDCLNIPNSTFQSLFRNAIGKVLCSKYEP 400
401 FYQSIDMTSVVRDYFSDSYLSDDPYLYADHSVLGEGVKIPLGRHKSLDPG 450
451 DISAISPILNKVIAEDHHEYTNSRLQYVLFLENRYWKKLRKIVQDLIIPT 500
501 LASSAVHKPMFTDQLVEIFPHMTRSVTFMDREPQLTSLRESVVQLFTCPT 550
551 TAYSIFHSGHFNYVIWSVIDVFVDFSTMDEGTLVWQRVQRSNPSKSYSIS 600
601 FKQGLYAVETLLSKITDPNLLLKPGEFIMIVTLCKLFNGAWKIKRKEGEH 650
651 VLREDQHFIPYLEYTTSVYSIIQTFDKVLQQSKDHIDQRLLIGAINLLDS 700
701 FLGHRNLSYKLYKDFEIIKFQISKERVSFMNPVHTLFSFLVQHVPLQVSI 750
751 QVLSQSKDYLVISDFALRSVVLCSQIDIGFWVRNGMSVLHQSAYYKNNPE 800
801 MSSYSRDIQLNQLAFLIEKNDFQRVIYNMLDRWELLDWFDGSVPSTETVY 850
851 DDKISSIIQQFVAFLYQILVERDFYKKFDTLEETQLYNIKNAIIYKLYAE 900
901 PLSYTDLLNDIPDYLTESVSQFDTVLEEVSTYIEPKGLEDNGVFKLKKEL 950
951 YKRIDSLRLLNMGNDFEHSATIVKSHLADSKEKRAKIIVKPQLLELDELD 1000
1001 PCARELGSFTRTNLFAKLIFKLLKLAVSDSSFSFTYELLHLIHAIFRDDE 1050
1051 MVNGKDSLPEAYISKPICDLLLSIVDSESGSFSENVVATADYLLDNMIMK 1100
1101 RPTAVLESLTECFGTKYIADYKIRKANQGVNFEETEQERKRRLAKNRQQQ 1150
1151 IMNRFSRQQKKFMDKHEEYSAGNDEDVDMDGEDLAGELNEFHCSLCHDDV 1200
1201 SDDFFVIPIYQNYSPVFLSSNPTPMEIYKPWHGFDNNEHLATYNTDLFYK 1250
1251 KKENGASQLMHESTQKVLVSCNHAVHYRCFKHYIDKKRYSTDLFICPLCQ 1300
1301 TYCNSVIPVDTVKLQSGDRLLQQKLTGGLDESLLLTFSEYSSECNDEVGK 1350
1351 IILSLKDSNNGLRLNRNDPTWIQDRFLTLSLQFSNNICMLEMLSRLNKDP 1400
1401 FGTLLSGEEQKFKTLQNILKSLAVYTRLTKHTEENVLKFYEDIRSSNLPS 1450
1451 YPFFRVVETVLRSRLSFKDCLQEVLVERLKGLTKDFGSFYRKYESELRAQ 1500
1501 TCLDSSEFSIVLKTTILGAGFGDQVEKHTLDLFYTFLISELLPTLRRSII 1550
1551 LLKALKQFMTGGDDLDFNEKDVLSGSLTSESKEKHFHLLIRFLLQTDFYD 1600
1601 LLMNSHSPLSPESSLVNAPHEYCSIIKLTDLATHLNTYVTNNKNITLREE 1650
1651 NDQKIRNTVNRLDYKICLICGVKIHARTDGLEMQKHMERCSHGSSGLFLI 1700
1701 PNISQVCLYLSRPDCTVNISAPYLNSHGESGRNAIERGDLTVLNHARYEH 1750
1751 LTRLWISNGIPGYISRVMGDEFRVAMANNRTFTRNMFWRPGAAFNAGGES 1800
1801 SDEDLMNDDEFGNDDRPDLRFRQPDVELRINGGPFGGDIPIRLPTERGDI 1850
1851 HDFFEFVQNMRGGMQGDGADIPTTEDIIEQLQGNAMNGFFGRADRNREHF 1900
1901 ELNDQSDGNEDGEDEEHENNASEDQDTEYSSAEEGFDFNELNNVE 1945
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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