 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P13542 from www.uniprot.org...
The NucPred score for your sequence is 0.95 (see score help below)
1 MSAGSDAEMAIFGEAAPYLRKSEKERIEAQNKPFDAKTSVFVAEPKESYV 50
51 KSVIQSKDGGKVTVKTESGATLTVKEDQVFPMNPPKYDKIEDMAMMTHLH 100
101 EPGVLYNLKERYAAWMIYTYSGLFCVTVNPYKWLPVYNPEVVAAYRGKKR 150
151 QEAPPHIFSISDNAYQFMLTDRENQSILITGESGAGKTVNTKRVIQYFAT 200
201 IAVTGDKKKEESGKMQGTLEDQIISANPLLEAFGNAKTVRNDNSSRFGKF 250
251 IRIHFGTTGKLASADIETYLLEKSRVTFQLKAERSYHIFYQITSNKKPEL 300
301 IEMLLITTNPYDYAFVSQGEITVPSIDDQEELMATDSAIDILGFSPEEKV 350
351 SIYKLTGAVMHYGNMKFKQKQREEQAEPDGTEVADKAAYLQCLNSADLLK 400
401 ALCYPRVKVGNEYVTKGQTVQQVYNAVGALAKAVYEKMFLWMVTRINQQL 450
451 DTKQPRQYFIGVLDIAGFEIFDFNSLEQLCINFTNEKLQQFFNHHMFVLE 500
501 QEEYKKEGIEWTFIDFGMDLAACIELIEKPLGIFSILEEECMFPKATDTS 550
551 FKNKLYDQHLGKSNNFQKPKPTKGKAEAHFSLVHYAGTVDYNITGWLDKN 600
601 KDPLNDTVVGLYQKSAMKTLASLFSTYASAEADGGAKKGAKKKGSSFQTV 650
651 SALFRENLNKLMTNLRSTHPHFVRCIIPNETKTPGAMEHELVLHQLRCNG 700
701 VLEGIRICRKGFPSRILYGDFKQRYKVLNASAIPEGQFIDSKKASEKLLG 750
751 SIDIDHTQYKFGHTKVFFKAGLLGLLEEMRDEKLAQIITRTQAVCRGYLM 800
801 RVEYQKMLLRRESIFCIQYNVRAFMNVKHWPWMKLFFKIKPLLKSAETEK 850
851 EMATMKEEFQKTKDELAKSEAKRKELEEKMVTLLKEKNDLQLQVQSEADS 900
901 LADAEERCEQLIKNKIQLEAKIKEVTERAEDEEEINAELTAKKRKLEDEC 950
951 SELKKDIDDLELTLAKVEKEKHATENKVKNLTEEMAGLDENIAKLTKEKK 1000
1001 ALQEAHQQTLDDLQAEEDKVNTLTKAKTKLEQQVDDLEGSLEQEKKLRMD 1050
1051 LERAKRKLEGDLKLAQESTMDIENDKQQLDEKLKKKEFEISNLISKIEDE 1100
1101 QAVEIQLQKKIKELQARIEELEEEIEAERASRAKAEKQRSDLSRELEEIS 1150
1151 ERLEEAGGATSAQVEMNKKRETEFQKLRRDLEEATLQHEATAAALRKKHA 1200
1201 DSVAELGEQIDNLQRVKQKLEKEKSELKMEIDDLSSNAEAIAKAKGNLEK 1250
1251 MCRTLEDQVSELKSKEEEQQRLINELTAQRARLQTEAGEYSRQLDEKDAL 1300
1301 VSQLSRSKQASTQQIEELKRQLEEETKAKNALAHALQSSRHDCDLLREQY 1350
1351 EEEQEGKAELQRALSKANSEVAQWRTKYETDAIQRTEELEEAKKKLAQRL 1400
1401 QAAEEHVEAVNAKCASLEKTKQRLQNEVEDLMIDVERTNAACAALDKKQR 1450
1451 NFDKVLSEWRQKYEETQAELESCQKESRTLSTELFKVKNAYEESLDHLET 1500
1501 LRRENKNLQQEISDLTEQIAEGGKHIHELEKIKKQVEQEKCEIQAALEEA 1550
1551 EASLEHEEGKILRIQLELNQVKSEIDRKIAEKDEEIDQLKRNHVRVVETM 1600
1601 QSTLDAEIRSRNDALRVKKKMEGDLNEMEIQLNHANRLAAESLRNYRNTQ 1650
1651 GILKDTQLHLDDALRGQEDLKEQLAIVERRANLLQAEIEELRATLEQTER 1700
1701 SRKIAEQELLDASERVQLLHTQNTSLINTKKKLENDVSQLQSEVEEVIQE 1750
1751 SRNAEEKAKKAITDAAMMAEELKKEQDTSAHLERMKKNMEQTVKDLQHRL 1800
1801 DEAEQLALKGGKKQIQKLEARVRELEGEVENEQKRNAEAVKGLRKHERRV 1850
1851 KELTYQTEEDRKNVLRLQDLVDKLQAKVKSYKRQAEEAEEQSNANLAKFR 1900
1901 KLQHELEEAEERADIAESQVNKLRVKSREVHTKISAE 1937
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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