 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q64612 from www.uniprot.org...
The NucPred score for your sequence is 0.28 (see score help below)
1 MRPLILLAALLWLQGFLAEDDACSSLEGSPDRQGGGPLLSVNVSSHGKST 50
51 SLFLSWVAAELGGFDYALSLRSVNSSGSPEGQQLQAHTNESGFEFHGLVP 100
101 GSRYQLKLTVLRPCWQNVTITLTARTAPTVVRGLQLHSAGSPARLEASWS 150
151 DAPGDQDSYQLLLYHLESQTLACNVSVSPDTLSYSFGDLLPGTQYVLEVI 200
201 TWAGSLHAKTSILQWTEPVPPDHLALRALGTSSLQAFWNSSEGATSFHLM 250
251 LTDLLGGTNTTAVIRQGVSTHTFLHLSPGTPHELKICASAGPHQIWGPSA 300
301 TEWTYPSYPSDLVLTPLRNELWASWKAGLGARDGYVLKLSGPMESTSTLG 350
351 PEECNAVFPGPLPPGHYTLQLKVLAGPYDAWVEGSTWLAESAALPREVPG 400
401 ARLWLDGLEASKQPGRRALLYSDDAPGSLGNISVPSGATHVIFCGLVPGA 450
451 HYRVDIASSTGDISQSISGYTSPLPPQSLEVISRSSPSDLTIAWGPAPGQ 500
501 LEGYKVTWHQDGSQRSPGDLVDLGPDTLSLTLKSLVPGSCYTVSAWAWAG 550
551 NLDSDSQKIHSCTRPAPPTNLSLGFAHQPAALKASWYHPPGGRDAFHLRL 600
601 YRLRPLTLESEKVLPREAQNFSWAQLTAGCEFQVQLSTLWGSERSSSANA 650
651 TGWTPPSAPTLVNVTSDAPTQLQVSWAHVPGGRSRYQVTLYQESTRTATS 700
701 IMGPKEDGTSFLGLTPGTKYKVEVISWAGPLYTAAANVSAWTYPLIPNEL 750
751 LVSMQAGSAVVNLAWPSGPLGQGACHAQLSDAGHLSWEQPLKLGQELFML 800
801 RDLTPGHTISMSVRCRAGPLQASTHLVVLSVEPGPVEDVLCHPEATYLAL 850
851 NWTMPAGDVDVCLVVVERLVPGGGTHFVFQVNTSGDALLLPNLMPTTSYR 900
901 LSLTVLGRNSRWSRAVSLVCSTSAEAWHPPELAEPPQVELGTGMGVTVMR 950
951 GMFGKDDGQIQWYGIIATINMTLAQPSREAINYTWYDHYYRGCESFLALL 1000
1001 FPNPFYPEPWAGPRSWTVPVGTEDCDNTQEICNGRLKSGFQYRFSVVAFS 1050
1051 RLNTPETILAFSAFSEPRASISLAIIPLTVMLGAVVGSIVIVCAVLCLLR 1100
1101 WRCLKGPRSEKDGFSKELMPYNLWRTHRPIPIHSFRQSYEAKSAHAHQTF 1150
1151 FQEFEELKEVGKDQPRLEAEHPDNIIKNRYPHVLPYDHSRVRLTQLPGEP 1200
1201 HSDYINANFIPGYSHTQEIIATQGPLKKTLEDFWRLVWEQQVHVIIMLTV 1250
1251 GMENGRVLCEHYWPANSTPVTHGHITIHLLAEEPEDEWTRREFQLQHGTE 1300
1301 QKQRRVKQLQFTTWPDHSVPEAPSSLLAFVELVQEQVQATQGKGPILVHC 1350
1351 SAGVGRTGTFVALLRLLRQLEEEKVADVFNTVYILRLHRPLMIQTLSQYI 1400
1401 FLHSCLLNKILEGPPDSSDSGPISVMDFAQACAKRAANANAGFLKEYKLL 1450
1451 KQAIKDGTGSLLPPPDYNQNSIVSRRHSQEQFALVEECPEDSMLEASLFP 1500
1501 GGPSGCDHVVLTGSAGPKELWEMVWEHDAHVLVSLGLPDTKEKPPDIWPV 1550
1551 EMQPIVTDMVTVHRVSESNTTTGWPSTLFRVIHGESGKERQVQCLQFPCS 1600
1601 ESGCELPANTLLTFLDAVGQCCFRGKSKKPGTLLSHSSKNTNQLGTFLAM 1650
1651 EQLLQQAGTERTVDVFNVALKQSQACGLMTPTLEQYIYLYNCLNSALLNG 1700
1701 LPRAGKWPAPC 1711
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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