 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8CG48 from www.uniprot.org...
The NucPred score for your sequence is 0.78 (see score help below)
1 MYVKSIILEGFKSYAQRTEVNGFDPLFNAITGLNGSGKSNILDSICFLLG 50
51 ISNLSQVRASNLQDLVYKNGQAGITKASVSITFDNSDKKQSPLGFEAHDE 100
101 ITVTRQVVIGGRNKYLINGVNANNTRVQDLFCSVGLNVNNPHFLIMQGRI 150
151 TKVLNMKPPEILSMIEEAAGTRMYEYKKIAAQKTIEKKEAKLKEIKTILE 200
201 EEITPTIQKLKEERSSYLEYQKVMREIEHLSRLYIAYQFLRAEDTKERSA 250
251 GELKEMQDKIVNLQEVLSENEKKIKALNCEIEELERRKDKETGGKLKSLE 300
301 DACAEAQRVNTKSQSAFDLKKKNLASEETKRKELQNSMAEDSKALAAKEK 350
351 EVKKITDGLHGLQEASNKDAEALAAAQQHFNAVSAGLSSNEDGAEATLAG 400
401 QMIACKNDISKAQTEAKQAQMKLKHAQQELKSKQAEVKKMDSGYKKDQDA 450
451 FEAVKKAKEKLETEMKKLNYEENKEEKLLEKHRQLSRDINNLKGKHEALL 500
501 AKFPNLQFAYKDPEKNWNRNSVKGLVASLINVKDNSTATALEVVAGERLY 550
551 NVVVDTEVTAKKLLEKGELKRRYTIIPLNKISARCIAPETLRVAQNLVGP 600
601 DNVHVALSLVDYKPELQKGMEFVFGTTFVCNNMDNAKKVAFDKRIMTRTV 650
651 TLGGDVFDPHGTLSGGARSQAASILTKFQEVKDVQDELRTKENELRALEE 700
701 ELAGLKNVAEKYRQLKQQWEMKTEEGDLLQTKLQQSSYHKQQEELDALKK 750
751 TIEESEETLKSTKEIQKKAEEKYEALENKMKNAEAEREKELKDAQKKLDC 800
801 AKTKADASSKKMKEKQQEVEAITLELEELKREHASNEQQLDAVNEAIKAY 850
851 EGQIEKMAAEVAKNKESVNKAQDELMKQKQIITAQDNIIKDKCAEVAKHN 900
901 LQNNESQLKIKELDHSISKHKREADDAAAKVSKMLSDYDWINAEKHLFGQ 950
951 PNSAYDFKTNNPKEAGQRLQKLQEVKEKLGRNVNLRAMNVLTEAEERYND 1000
1001 LMKKKRIVENDKSKILATIEDLDQKKNQALNIAWQKVNKDFGSIFSTLLP 1050
1051 GANAMLAPPEGQTVLDGLEFKVALGNTWKENLTELSGGQRSLVALSLILS 1100
1101 MLLFKPAPIYILDEVDAALDLSHTQNIGQMLRTHFTHSQFIVVSLKEGMF 1150
1151 NNANVLFKTKFVDGVSTVARFTQSQAGKIPKEAKSRGKEPN 1191
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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