 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P12847 from www.uniprot.org...
The NucPred score for your sequence is 0.94 (see score help below)
1 MSSDTEMEVFGIAAPFLRKSEKERIEAQNQPFDAKTYCFVVDSKEEYAKG 50
51 KIKSSQDGKVTVETEDNRTLVVKPEDVYAMNPPKFDKIEDMAMLTHLNEP 100
101 AVLYNLKDRYTSWMIYTYSGLFCVTVNPYKWLPVYTPEVVDGYRGKKRQE 150
151 APPHIFSISDNAYQFMLTDRENQSILITGESGAGKTVNTKRVIQYFATIA 200
201 ATGDLAKKKDSKMKGTLEDQIISANPLLEAFGNAKTVRNDNSSRFGKFIR 250
251 IHFGTTGKLASADIETYLLEKSRVTFQLKAERSYHIFYQILSNKKPELIE 300
301 LLLITTNPYDYPFISQGEILVASIDDREELLATDSAIDILGFTPEEKSGL 350
351 YKLTGAVMHYGNMKFKQKQREEQAEPDGTEVADKTAYLMGLNSSDLLKAL 400
401 CFPRVKVGNEYVTKGQTVDQVHHAVNALSKSVYEKLFLWMVTRINQQLDT 450
451 KLPRQHFIGVLDIAGFEIFEYNSLEQLCINFTNEKLQQFFNHHMFVLEQE 500
501 EYKKEGIEWTFIDFGMDLAACIELIEKPMGIFSILEEECMFPKATDTSFK 550
551 NKLYDQHLGKSNNFQKPKVVKGKAEAHFSLIHYAGTVDYSVSGWLEKNKD 600
601 PLNETVVGLYQKSSNRLLAHLYATFATTDADGGKKKVAKKKGSSFQTVSA 650
651 LFRENLNKLMSNLRTTHPHFVRCIIPNETKTPGAMEHSLVLHQLRCNGVL 700
701 EGIRICRKGFPNRILYGDFKQRYRVLNASAIPEGQFIDSKKACEKLLASI 750
751 DIDHTQYKFGHTKVFFKAGLLGTLEEMRDERLAKLITRTQAVCRGFLMRV 800
801 EFQKMMQRRESIFCIQYNIRAFMNVKHWPWMKLFFKIKPLLKSAETEKEM 850
851 ATMKEEFQKTKDELAKSEAKRKELEEKLVTLVQEKNDLQLQVQAESENLL 900
901 DAEERCDQLIKAKFQLEAKIKEVTERAEDEEEINAELTAKKRKLEDECSE 950
951 LKKDIDDLELTLAKVEKEKHATENKVKNLTEELAGLDETIAKLTREKKAL 1000
1001 QEAHQQTLDDLQAEEDKVNSLSKLKSKLEQQVDDLESSLEQEKKLRVDLE 1050
1051 RNKRKLEGDLKLAQESILDLENDKQQLDERLKKKDFEYSQLQSKVEDEQT 1100
1101 LSLQLQKKIKELQARIEELEEEIEAERATRAKTEKQRSDYARELEELSER 1150
1151 LEEAGGVTSTQIELNKKREAEFLKLRRDLEEATLQHEATVATLRKKHADS 1200
1201 AAELAEQIDNLQRVKQKLEKEKSEFKLEIDDLSSSVESVSKSKANLEKIC 1250
1251 RTLEDQLSEARGKNEETQRSLSELTTQKSRLQTEAGELSRQLEEKESIVS 1300
1301 QLSRSKQAFTQQIEELKRQLEEENKAKNALAHALQSSRHDCDLLREQYEE 1350
1351 EQEGKAELQRALSKANSEVAQWRTKYETDAIQRTEELEEAKKKLAQRLQD 1400
1401 SEEQVEAVNAKCASLEKTKQRLQGEVEDLMVDVERANSLAAALDKKQRNF 1450
1451 DKVLAEWKTKCEESQAELEAALKESRSLSTELFKLKNAYEEALDQLETVK 1500
1501 RENKNLEQEIADLTEQIAENGKSIHELEKSRKQMELEKADIQMALEEAEA 1550
1551 ALEHEEAKILRIQLELTQVKSEIDRKIAEKDEEIEQLKRNYQRTVETMQG 1600
1601 ALDAEVRSRNEAIRLKKKMEGDLNEIEIQLSHANRQAAETIKHLRSVQGQ 1650
1651 LKDTQLHLDDALRGQEDLKEQLAIVERRANLLQAEVEELRATLEQTERAR 1700
1701 KLAEQELLDSNERVQLLHTQNTSLIHTKKKLETDLTQLQSEVEDASRDAR 1750
1751 NAEEKAKKAITDAAMMAEELKKEQDTSAHLERMKKNLEQTVKDLQHRLDE 1800
1801 AEQLALKGGKKQIQKLETRIRELEFELEGEQKRNTESVKGLRKYERRVKE 1850
1851 LTYQSEEDRKNVLRLQDLVDKLQVKVKSYKRQAEEADEQANVHLTKFRKA 1900
1901 QHELEEAEERADIAESQVNKLRAKTRDFTSSRMVVHESEE 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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