 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P13538 from www.uniprot.org...
The NucPred score for your sequence is 0.95 (see score help below)
1 MASPDAEMAAFGEAAPYLRKSEKERIEAQNKPFDAKSSVFVVHPKESFVK 50
51 GTIQSKEGGKVTVKTEGGETLTVKEDQVFSMNPPKYDKIEDMAMMTHLHE 100
101 PAVLYNLKERYAAWMIYTYSGLFCVTVNPYKWLPVYNPEVVLAYRGKKRQ 150
151 EAPPHIFSISDNAYQFMLTDRENQSILITGESGAGKTVNTKRVIQYFATI 200
201 AASGEKKKEEQSGKMQGTLEDQIISANPLLEAFGNAKTVRNDNSSRFGKF 250
251 IRIHFGATGKLASADIETYLLEKSRVTFQLPAERSYHIFYQIMSNKKPEL 300
301 IDMLLITTNPYDYHYVSQGEITVPSIDDQEELMATDSAIDILGFSADEKT 350
351 AIYKLTGAVMHYGNLKFKQKQREEQAEPDGTEVADKAAYLMGLNSAELLK 400
401 ALCYPRVKVGNEFVTKGQTVSQVHNSVGALAKAVYEKMFLWMVIRINQQL 450
451 DTKQPRQYFIGVLDIAGFEIFDFNSFEQLCINFTNEKLQQFFNHHMFVLE 500
501 QEEYKKEGIEWEFIDFGMDLAACIELIEKPMGIFSILEEECMFPKATDTS 550
551 FKNKLYDQHLGKSNNFQKPKPAKGKAEAHFSLVHYAGTVDYNISGWLEKN 600
601 KDPLNETVIGLYQKSSVKTLALLFATYGGEAEGGGGKKGGKKKGSSFQTV 650
651 SALFRENLNKLMANLRSTHPHFVRCIIPNETKTPGAMEHELVLHQLRCNG 700
701 VLEGIRICRKGFPSRVLYADFKQRYRVLNASAIPEGQFMDSKKASEKLLG 750
751 SIDVDHTQYRFGHTKVFFKAGLLGLLEEMRDDKLAEIITRTQARCRGFLM 800
801 RVEYRRMVERRESIFCIQYNVRSFMNVKHWPWMKLFFKIKPLLKSAESEK 850
851 EMANMKEEFEKTKEELAKSEAKRKELEEKMVVLLQEKNDLQLQVQAEADS 900
901 LADAEERCDQLIKTKIQLEAKIKEVTERAEDEEEINAELTAKKRKLEDEC 950
951 SELKKDIDDLELTLAKVEKEKHATENKVKNLTEEMAVLDETIAKLTKEKK 1000
1001 ALQEAHQQTLDDLQVEEDKVNTLTKAKTKLEQQVDDLEGSLEQEKKLRMD 1050
1051 LERAKRKLEGDLKLAHDSIMDLENDKQQLDEKLKKKDFEISQIQSKIEDE 1100
1101 QALGMQLQKKIKELQARIEELEEEIEAERTSRAKAEKHRADLSRELEEIS 1150
1151 ERLEEAGGATAAQIEMNKKREAEFQKMRRDLEEATLQHEATAAALRKKHA 1200
1201 DSTAELGEQIDNLQRVKQKLEKEKSELKMEIDDLASNMESVSKAKANLEK 1250
1251 MCRTLEDQLSEIKTKEEQNQRMINDLNTQRARLQTETGEYSRQAEEKDAL 1300
1301 ISQLSRGKQGFTQQIEELKRHLEEEIKAKNALAHALQSARHDCELLREQY 1350
1351 EEEQEAKGELQRALSKANSEVAQWRTKYETDAIQRTEELEEAKKKLAQRL 1400
1401 QDAEEHVEAVNAKCASLEKTKQRLQNEVEDLMVDVERSNAACAALDKKQK 1450
1451 NFDKILAEWKQKYEETQTELEASQKESRSLSTELFKMKNAYEESLDHLET 1500
1501 LKRENKNLQQEIADLTEQIAEGGKAVHELEKVKKHVEQEKSELQASLEEA 1550
1551 EASLEHEEGKILRLQLELNQIKSEIDRKIAEKDEEIDQLKRNHLRIVESM 1600
1601 QSTLDAEIRSRNEALRLKKKMEGDLNEMEIQLSHANRMAAEAQKNLRNTQ 1650
1651 GTLKDTQIHLDDALRTQEDLKEQVAMVERRANLLQAEVEELRGALEQTER 1700
1701 SRKVAEQELLDATERVQLLHTQNTSLINTKKKLETDIVQIQSEMEDTIQE 1750
1751 ARNAEEKAKKAITDAAMMAEELKKEQDTSAHLERMKKNMDQTVKDLHVRL 1800
1801 DEAEQLALKGGKKQLQKLEARVRELEGEVDSEQKRSAEAVKGVRKYERRV 1850
1851 KELTYQCEEDRKNILRLQDLVDKLQMKVKSYKRQAEEAEELSNVNLSKFR 1900
1901 KIQHELEEAEERADIAESQVNKLRVKSREIHGKKIEEEE 1939
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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