 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P02565 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MATDADMAIFGEAAPYLRKSEKERIEAQNKPFDAKSSVFVVHAKESYVKS 50
51 TIQSKESGKVTVKTEGGETLTVKEDQIFSMNPPKYDKIEDMAMMTHLHEP 100
101 AVLYNLKERYAAWMIYTYSGLFCVTVNPYKWLPVYNPEVVLAYRGKKRQE 150
151 APPHIFSISDNAYQFMLTDRENQSILITGESGAGKTVNTKRVIQYFATIA 200
201 ASGDKKKEEQPAGKMQGTLEDQIISANPLLEAFGNAKTVRNDNSSRFGKF 250
251 IRIHFGATGKLASADIETYLLEKSRVTFQLKAERSYHIFYQIMSNKKPEL 300
301 IEMLLITTNPYDYQYVSQGEITVPSINDQEELMATDSAIDILGFTPDEKT 350
351 AIYKLTGAVMHYGNLKFKQKQREEQAEPGGTEVADKAAYLMGLNSADLLK 400
401 ALCYPRVKVGNEYVTKGQTVQQVYNSVGALAKSVFEKMFLWMVVRINQQL 450
451 DTKQPRQYFIGVLDIAGFEIFDFNSLEQLCINFTNEKLQQFFNHHMFVLE 500
501 QEEYKKEGIEWEFIDFGMDLAACIELIEKPMGIFSILEEECMFPKATDTS 550
551 FKNKLYDQHLGKSNNFQKPKPGKGKAEAHFSLVHYAGTVDYNITGWLEKN 600
601 KDPLNETVVGLYQKSSLKTLALLFASVGGAEAESGAGGKKGGKKKGSSFQ 650
651 TVSALFRENLNKLMSNLRSTHPHFVRCLIPNETKTPGAMEHELVLHQLRC 700
701 NGVLEGIRICRKGFPIRILYADFKQRYKVLNASAIPEGQFIDSKKASEKL 750
751 LGSIDVDHTQYKFGHTKVFFKAGLLGLLEEMRDEKLAQLITRTQARCRGF 800
801 LMRVEFKKMMERRESIFCIQYNVRAFMNVKHWPWMKLFFKIKPLLKSAES 850
851 EKEMANMKEEFEKTKEELAKSEAKRKELEEKMVSLLQEKNDLQLQVQAEA 900
901 DGLADAEERCDQLIKTKIQLEAKIKELTERAEDEEEMNAELTAKKRKLED 950
951 ECSELKKDIDDLELTLAKVEKEKHATENKVKNLTEEMAALDETIAKLTKE 1000
1001 KKALQEAHQQTLDDLQAEEDKVNTLTKAKTKLEQQVDDLEGSLEQEKKLR 1050
1051 MDLERAKRKLEGDLKMTQESTMDLENDKQQLDEKLKKKDFEISQIQSKIE 1100
1101 DEQALGMQLQKKIKELQARIEELEEEIEAERTSRAKAEKHRADLSRELEE 1150
1151 ISERLEEAGGATAAQIDMNKKREAEFQKMRRDLEEATLQHEATAAALRKK 1200
1201 HADSTADVGEQIDNLQRVKQKLEKEKSELKMEIDDLASNMESVSKAKANL 1250
1251 EKMCRSLEDQLSEIKTKEEEQQRTINDISAQKARLQTESGEYSRQVEEKD 1300
1301 ALISQLSRGKQAFTQQIEELKRHLEEEIKAKKCPAHALQSARHDCDLLRE 1350
1351 QYEEEQEAKGELQRALSKANSEVAQWRTKYETDAIQRTEELEEAKKKLAQ 1400
1401 RLQDAEEHVEAVNSKCASLEKTKQRLQNEVEDLMIDVERSNAACAALDKK 1450
1451 QKNFDKILSEWKQKYEETQAELEASQKESRSLSTELFKMKNAYEESLDHL 1500
1501 ETLKRENKNLQQEISDLTEQIAEGGKAIHELEKVKKQIEQEKSELQTALE 1550
1551 EAEASLEHEEGKILRVQLELNQVKSDIDRKIAEKDEEIDQLKRNHLRVVD 1600
1601 SMQSTLDAEIRSRNEALRLKKKMEGDLNEIEIQLSHANRQAAEAQKNLRN 1650
1651 TQGVLKDTQIHLDDALRSQEDLKEQVAMVERRANLLQAEIEELRAALEQT 1700
1701 ERSRKVAEQELLDASERVQLLHTQNTSLINTKKKLESDISQIQSEMEDTI 1750
1751 QEARNAEEKAKKAITDAAMMAEELKKEQDTSAHLERMKKNLDQTVKDLQH 1800
1801 RLDEAEQLALKGGKKQIQKLEARVRELEGEVDAEQKRSAEAVKGVRKYER 1850
1851 RVKELTYQSEEDRKNVLRLQDLVDKLQMKVKSYKRQAEEAEELSNVNLSK 1900
1901 FRKIQHELEEAEERADIAESQVNKLRAKSREIGKKAESEE 1940
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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