 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O95347 from www.uniprot.org...
The NucPred score for your sequence is 0.82 (see score help below)
1 MHIKSIILEGFKSYAQRTEVNGFDPLFNAITGLNGSGKSNILDSICFLLG 50
51 ISNLSQVRASNLQDLVYKNGQAGITKASVSITFDNSDKKQSPLGFEVHDE 100
101 ITVTRQVVIGGRNKYLINGVNANNTRVQDLFCSVGLNVNNPHFLIMQGRI 150
151 TKVLNMKPPEILSMIEEAAGTRMYEYKKIAAQKTIEKKEAKLKEIKTILE 200
201 EEITPTIQKLKEERSSYLEYQKVMREIEHLSRLYIAYQFLLAEDTKVRSA 250
251 EELKEMQDKVIKLQEELSENDKKIKALNHEIEELEKRKDKETGGILRSLE 300
301 DALAEAQRVNTKSQSAFDLKKKNLACEESKRKELEKNMVEDSKTLAAKEK 350
351 EVKKITDGLHALQEASNKDAEALAAAQQHFNAVSAGLSSNEDGAEATLAG 400
401 QMMACKNDISKAQTEAKQAQMKLKHAQQELKNKQAEVKKMDSGYRKDQEA 450
451 LEAVKRLKEKLEAEMKKLNYEENKEESLLEKRRQLSRDIGRLKETYEALL 500
501 ARFPNLRFAYKDPEKNWNRNCVKGLVASLISVKDTSATTALELVAGERLY 550
551 NVVVDTEVTGKKLLERGELKRRYTIIPLNKISARCIAPETLRVAQNLVGP 600
601 DNVHVALSLVEYKPELQKAMEFVFGTTFVCDNMDNAKKVAFDKRIMTRTV 650
651 TLGGDVFDPHGTLSGGARSQAASILTKFQELKDVQDELRIKENELRALEE 700
701 ELAGLKNTAEKYRQLKQQWEMKTEEADLLQTKLQQSSYHKQQEELDALKK 750
751 TIEESEETLKNTKEIQRKAEEKYEVLENKMKNAEAERERELKDAQKKLDC 800
801 AKTKADASSKKMKEKQQEVEAITLELEELKREHTSYKQQLEAVNEAIKSY 850
851 ESQIEVMAAEVAKNKESVNKAQEEVTKQKEVITAQDTVIKAKYAEVAKHK 900
901 EQNNDSQLKIKELDHNISKHKREAEDGAAKVSKMLKDYDWINAERHLFGQ 950
951 PNSAYDFKTNNPKEAGQRLQKLQEMKEKLGRNVNMRAMNVLTEAEERYND 1000
1001 LMKKKRIVENDKSKILTTIEDLDQKKNQALNIAWQKVNKDFGSIFSTLLP 1050
1051 GANAMLAPPEGQTVLDGLEFKVALGNTWKENLTELSGGQRSLVALSLILS 1100
1101 MLLFKPAPIYILDEVDAALDLSHTQNIGQMLRTHFTHSQFIVVSLKEGMF 1150
1151 NNANVLFKTKFVDGVSTVARFTQCQNGKISKEAKSKAKPPKGAHVEV 1197
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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