 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P13535 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MSASSDAEMAVFGEAAPYLRKSEKERIEAQNKPFDAKTSVFVAEPKESYV 50
51 KSTIQSKEGGKVTVKTEGGATLTVREDQVFPMNPPKYDKIEDMAMMTHLH 100
101 EPGVLYNLKERYAAWMIYTYSGLFCVTVNPYKWLPVYKPEVVAAYRGKKR 150
151 QEAPPHIFSISDNAYQFMLTDRENQSILITGESGAGKTVNTKRVIQYFAT 200
201 IAVTGEKKKDESGKMQGTLEDQIISANPLLEAFGNAKTVRNDNSSRFGKF 250
251 IRIHFGTTGKLASADIETYLLEKSRVTFQLKAERSYHIFYQITSNKKPDL 300
301 IEMLLITTNPYDYAFVSQGEITVPSIDDQEELMATDSAIDILGFTPEEKV 350
351 SIYKLTGAVMHYGNMKFKQKQREEQAEPDGTEVADKAAYLQSLNSADLLK 400
401 ALCYPRVKVGNEYVTKGQTVQQVYNAVGALAKAVYEKMFLWMVTRINQQL 450
451 DTKQPRQYFIGVLDIAGFEIFDFNSLEQLCINFTNEKLQQFFNHHMFVLE 500
501 QEEYKKEGIEWTFIDFGMDLAACIELIEKPLGIFSILEEECMFPKATDTS 550
551 FKNKLYDQHLGKSANFQKPKVVKGKAEAHFSLIHYAGTVDYNITGWLDKN 600
601 KDPLNDTVVGLYQKSAMKTLASLFSTYASAEADSSAKKGAKKKGSSFQTV 650
651 SALFRENLNKLMTNLRSTHPHFVRCIIPNETKTPGAMEHELVLHQLRCNG 700
701 VLEGIRICRKGFPSRILYGDFKQRYKVLNASAIPEGQFIDSKKASEKLLA 750
751 SIDIDHTQYKFGHTKVFFKAGLLGLLEEMRDEKLAQIITRTQAVCRGFLM 800
801 RVEYQKMLQRREALFCIQYNVRAFMNVKHWPWMKLFFKIKPLLKSAETEK 850
851 EMATMKEEFQKTKDELAKSEAKRKELEEKMVTLLKEKNDLQLQVQSEADS 900
901 LADAEERCEQLIKNKIQLEAKIKEVTERAEEEEEINAELTAKKRKLEDEC 950
951 SELKKDIDDLELTLAKVEKEKHATENKVKNLTEEMAGLDETIAKLSKEKK 1000
1001 ALQETHQQTLDDLQAEEDKVNILTKAKTKLEQQVDDLEGSLEQEKKLRMD 1050
1051 LERAKRKLEGDLKLAQESTMDMENDKQQLDEKLEKKEFEISNLISKIEDE 1100
1101 QAVEIQLQKKIKELQARIEELGEEIEAERASRAKAEKQRSDLSRELEEIS 1150
1151 ERLEEAGGATSAQVELNKKREAEFQKLRRDLEEATLQHEAMVAALRKKHA 1200
1201 DSMAELGEQIDNLQRVKQKLEKEKSELKMETDDLSSNAEAISKAKGNLEK 1250
1251 MCRSLEDQVSELKTKEEEQQRLINDLTAQRARLQTEAGEYSRQLDEKDAL 1300
1301 VSQLSRSKQASTQQIEELKHQLEEETKAKNALAHALQSSRHDCDLLREQY 1350
1351 EEEQEGKAELQRALSKANSEVAQWRTKYETDAIQRTEELEEAKKKLAQRL 1400
1401 QEAEEHVEAVNAKCASLEKTKQRLQNEVEDLMLDVERSNAACAALDKKQR 1450
1451 NFDKVLSEWKQKYEETQAELEASQKESRSLSTELFKVKNVYEESLDQLET 1500
1501 LRRENKNLQQEISDLTEQIAEGGKQIHELEKIKKQVEQEKCEIQAALEEA 1550
1551 EASLEHEEGKILRIQLELNQVKSEVDRKIAEKDEEIDQLKRNHTRVVETM 1600
1601 QSTLDAEIRSRNDALRVKKKMEGDLNEMEIQLNHANRLAAESLRNYRNTQ 1650
1651 GILKETQLHLDDALRGQEDLKEQLAIVERRANLLQAEIEELWATLEQTER 1700
1701 SRKIAEQELLDASERVQLLHTQNTSLINTKKKLENDVSQLQSEVEEVIQE 1750
1751 SRNAEEKAKKAITDAAMMAEELKKEQDTSAHLERMKKNLEQTVKDLQHRL 1800
1801 DEAEQLALKGGKKQIQKLEARVRELEGEVENEQKRNAEAVKGLRKHERRV 1850
1851 KELTYQTEEDRKNVLRLQDLVDKLQAKVKSYKRQAEEAEEQSNANLSKFR 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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