 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P70289 from www.uniprot.org...
The NucPred score for your sequence is 0.29 (see score help below)
1 MRPLILLAALLWLQDSLAQEDVCSSLDGSPDRQGGGPPLSVSVTSRGRPT 50
51 SLFLSWVAAEPGGFDYALCLRAMNLSGFPEGQQLQAHTNESSFEFHGLVP 100
101 GSRYQLELTVLRPCWQNVTITLTARTAPTVVRGLQLHSTGSPASLEASWS 150
151 DASGDQDSYQLLLYHPESHTLACNVSVSPDTLSYNFGDLLPGSQYVLEVI 200
201 TWAGSLHAKTSILQWTEPVPPDHLRVRALGTSSLQAFWNSSEGATWFHLI 250
251 LTDLLEGTNLTKVVRQGISTHTFLRLSPGTPYQLKICAAAGPHQIWGPNA 300
301 TEWTYPSYPSDLVLTPLWNELWASWKAGQGARDGYVLKLSGPVENTTTLG 350
351 PEECNAVFPGPLPPGHYTLGLRVLAGPYDAWVEGSIWLAESAARPMEVPG 400
401 ARLWLEGLEATKQPGRRALLYSVDAPGLLGNISVSSGATHVTFCGLVPGA 450
451 HYRVDIASSMGDITQSLTGYTSPLPPQSLEIISRNSPSDLTIGWAPAPGQ 500
501 MEGYKVTWHQDGSQRSPGDLVDLGPDISSLTLKSLVPGSCYTVSAWAWSG 550
551 NLSSDSQKIHSCTRPAPPTNLSLGFAHQPATLRASWCHPPGGRDAFQLRL 600
601 YRLRPLTLESEKILSQEAQNFSWAQLPAGYEFQVQLSTLWGSEESGSANT 650
651 TGWTPPSAPTLVNVTSEAPTQLHVSWVHAAGDRSSYQVTLYQESTRTATS 700
701 IVGPKADSTSFWGLTPGTKYKVEAISWAGPLYTAAANVSAWTYPLTPNEL 750
751 LASMQAGSAVVNLAWPSGPLGRGTCHAQLSDAGHLSWEQPLSLGQDLLML 800
801 RNLIPGHTVSLSVKCRAGPLQASTHPLVLSVEPGPVEDVFCQPEATYLSL 850
851 NWTMPTGDVAVCLVEVEQLVPGGSAHFVFQVNTSEDALLLPNLTPTTSYR 900
901 LSLTVLGGNRQWSRAVTLVCTTSAEVWHPPELAEAPQVELGTGMGVTVTR 950
951 GMFGKDDGQIQWYGIIATINMTLAQPSQEAINHTWYDHYYRGHDSYLALL 1000
1001 FPNPFYPEPWAVPRSWTVPVGTEDCDNTQEICNGHLKPGFQYRFSIAAFS 1050
1051 RLSSPETILAFSAFSEPQASISLVAMPLTVMMGTVVGCIIIVCAVLCLLC 1100
1101 RRGLKGPRSEKNGFSQELMPYNLWRTHRPIPSHSFRQSYEAKSARAHQAF 1150
1151 FQEFEELKEVGKDQPRLEAEHPANITKNRYPHVLPYDHSRVRLTQLSGEP 1200
1201 HSDYINANFIPGYSHPQEIIATQGPLKKTVEDFWRLVWEQQVHVIIMLTV 1250
1251 GMENGRVLCEHYWPVNSTPVTHGHITTHLLAEESEDEWTRREFQLQHGAE 1300
1301 QKQRRVKQLQFTTWPDHSVPEAPSSLLAFVELVQEEVKATQGKGPILVHC 1350
1351 SAGVGRTGTFVALLPAVRQLEEEQVVDVFNTVYILRLHRPLMIQTLSQYI 1400
1401 FLHSCLLNKILEGPSDASDSGPIPVMNFAQACAKRAANANAGFLKEYRLL 1450
1451 KQAIKDETGSLLPSPDYNQNSIASCHHSQEQLALVEESPADNMLAASLFP 1500
1501 GGPSGRDHVVLTGSAGPKELWEMVWEHGAYVLVSLGLPDTKEKPQDIWPM 1550
1551 EMQPIVTDMVTVHRVAESNTAGWPSTLIRVIHGDSGTERQVQCLQFPHCE 1600
1601 TGSELPANTLLTFLDAVGQCCSRGNSKKPGTLLSHSSKVTNQLSTFLAME 1650
1651 QLLQQAGTERTVDVFSVALKQTQACAVKTPTLEQYIYLYNCLNSALRNRL 1700
1701 PRARK 1705
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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