 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q90339 from www.uniprot.org...
The NucPred score for your sequence is 0.88 (see score help below)
1 MGDGEMECFGPAAVYLRKTERERIEAQNTPFDAKTAFFVVDPDEMYLKGT 50
51 LVSKEGGKATVKTHSGKTVTVKEDEIFPMNPPKFDKIEDMAMMTHLNEPA 100
101 VLFNLKERYAAWMIYTYSGLFCVTVNPYKWLPVYDAVVVGGYRGKKRIEA 150
151 PPHIFSISDNAYQFMLTDRENQSVLITGESGAGKTVNTKRVIQYFATVGA 200
201 MSGPKKPEPVPGKMQGSLEDQIVAANPLLEAYGNAKTVRNDNSSRFGKFI 250
251 RIHFGTTGKLASADIETYLLEKSRVTFQLSAERSYHIFYQLMTGHKPELL 300
301 EALLITTNPYDYPMISQGEITVKSINDVEEFIATDTAIDILGFTADEKIS 350
351 IYKLTGAVMHHGNMKFKQKQREEQAEPDGTEVADKIAYLMGLNSADMLKA 400
401 LCFPRVKVGNEMVTKGQTVPQVNNAVSALSKSVYEKMFLWMVIRINEMLD 450
451 TKQPRQFFIGVLDIAGFEIFDFNSLEQLCINFTNEKLQQFFNHHMFVLEQ 500
501 EEYKKEGIEWEFIDFGMDLAACIELIEKPMGIFSILEEECMFPKATDTSF 550
551 KNKLHDQHLGKTAAFQKPKPAKGKAEAHFSLVHYAGTVDYNIVGWLDKNK 600
601 DPLNDSVVQLYQKSSLKVLAFLYATHGAEAEGGGGKKGKKKGGSFQTVSA 650
651 LFRENLGKLMTNLRSTHPHFVRCLIPNESKTPGLMENYLVIHQLRCNGVL 700
701 EGIRICRKGFPSRILYGDFKQRYKVLNASVIPEGQFIDNKKASEKLLGSI 750
751 DVDHTQYKFGHTKVFFKAGLLGALEEMRDEKLALLVTMTQALCRGYVMRK 800
801 EFVKMMERRESIYSIQYNIRSFMNVKHWPWMKLYFKIKPLLKSAETEKEM 850
851 AAMKENYEKMKEDLTKALAKKKELEEKMVSLLQEKNDLQLQVTAESENLS 900
901 DAEERCEGLIKSKIQLEAKLKETNERLEDEEEINAELTAKKRKLEDECSE 950
951 LKKDIDDLELTLAKVEKEKHATENKVKNLTEEMASQDESIAKLTKEKKAL 1000
1001 QEAHQQTLDDLQAEEDKVNTLTKAKTKLEQQVDDLEGSLEQEKKLRMDLE 1050
1051 RAKRKLEGDLKLAQESIMDLENEKQQSDEKIKKKDFEISQLLSKIEDEQS 1100
1101 LGAQLQKKIKELQARIEELEEEIEAERAARAKVEKQRADLSRELEEISER 1150
1151 LEEAGGATAAQIEMNKKREAEFQKMRRDLEESTLQHEATAAALRKEQADS 1200
1201 VAELGEQIDNLQRVKQKLEKEKSEYKMEIDDLTSNMEAVAKAKANLEKMC 1250
1251 RTLEDQLSEIKTKSDENVRQLNDMNAQRARLQTENGEFSRQLEEKEALVS 1300
1301 QLTRGKQAYTQQIEELKRHIEEEVKAKNALAHAVQSARHDCDLLREQYEE 1350
1351 EQEAKAELQRGMSKANSEVAQWRTKYETDAIQRTEELEEAKKKLAQRLQD 1400
1401 AEESIEAVNSKCASLEKTKQRLQGEVEDLMIDVERANSLAANLDKKQRNF 1450
1451 DKVLAEWKQKYEESQAELEGAQKEARSLSTELFKMKNSYEEALDHLETLK 1500
1501 RENKNLQQEISDLTEQLGETGKSIHELEKAKKTVESEKSEIQTALEEAEG 1550
1551 TLEHEESKILRVQLELNQVKSEIDRKLAEKDEEMEQIKRNSQRVIDSMQS 1600
1601 TLDSEVRSRNDALRVKKKMEGDLNEMEIQLSHANRQAAEAQKQLRNVQGQ 1650
1651 LKDAQLHLDEAVRGQEDMKEQVAMVERRNSLMQAEIEELRAALEQTERGR 1700
1701 KVAEQELVDASERVGLLHSQNTSLINTKKKLEADLVQVQGEVDDAVQEAR 1750
1751 NAEEKAKKAITDAAMMAEELKKEQDTSAHLERMKKNLEVTVKDLQHRLDE 1800
1801 AESLAMKGGKKQLQKLESRVRELEAEVEAEQRRGADAVKGVRKYERRVKE 1850
1851 LTYQTEEDKKNVIRLQDLVDKLQLKVKVYKRQAEEAEEQTNTHLSRYRKV 1900
1901 QHELEEAQERADVAESQVNKLRAKSRDAGKSKDEE 1935
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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