 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P23466 from www.uniprot.org...
The NucPred score for your sequence is 0.95 (see score help below)
1 MSSPTDAERVNMRREKHPQIEETFEEHVHNAMPKFKKHYALGITTHTNDE 50
51 DDDPRDHRQRGIHNPNFIHSPNDPRPPLSQPIKPRFSVHGTASNASVFSH 100
101 GDIAPVRKTSRAGSLFKRLAGKKSTTSLLGTEHQQRQQQQSSNSLVPAAG 150
151 LRRKMSTFIHGGSGSQSNESRGTRSSIFFPSTSNSRRGSATSTMTSGSRS 200
201 SHPPDTPPITSQQQEQQYDQQRQQRPETREQEQKPPTLSDMPIVSRSPSF 250
251 FMLDTDLNNLSDITNIISATPKNTESDEVRSTGANKTLKYPKPPLSSHKS 300
301 TSASDLSHHKAQWTAPESWDIEEDANKLLATKRKAKHHHHYHHPQHPRPP 350
351 HRKHYSNFSKPIEDKAVVEKEQEPPEKCPQPISTDSNDAQGLEIAKPIDE 400
401 SSGIQHSASTQSVSSFSSGATGASGATGKQIGGDQETESTISTVGEDEEV 450
451 TNLRSIDSEQTDDTSFSKFDEEYDKAEYQLEKYYNDFSDVDLNRRYAIRI 500
501 FNIDDTFTTLSCTPNTTLQDMMPQLKRKFNVGQGSYQVSLKVGKLSKILR 550
551 PTAKPILIQRRLLLLNGYLKSDPLHIMGIEDLSFIFSFVFHPVATSHLNY 600
601 EQEQRLSRGDFVHVDLRNMDLTTPPIILYQHTSDIESLDVSNNANIFLPL 650
651 DFIESAIKLSSLRMVNIRASKFPANVTDAYKLVSLDLERNFIKKVPDSIF 700
701 KLNNLTIVNLQCNNLERLPPGFSKLKNLQLLDISSNKFVNYPEVINSCTN 750
751 LLQIDLSYNKIHSLPVSINQLVKLAKMNLFNNRLTSVGDLSQMKNLRTLN 800
801 LRCNRVTSIECHAPNLQNLFLTDNRISTFDDDLTRLRTLELQQNPITSMV 850
851 CGGNYMANMTSLSLNKAKLSSFSAELLSKLPRLEKLELNENNLTQLPPEI 900
901 NKLTRLIYLSVARNKLESIPDEISDLRSLKSLDLHSNNLRMLMNNLEDLE 950
951 LTSLNVSSNLLTGFHGSPAKFFASPSPKLAKSLLFLSVADNNLTDSIWPL 1000
1001 VNTFQNLKTLNLSYNNFVEISDLKLQNLTELYLSGNNFTSLPGEAVQHLR 1050
1051 SLKVLMLNGNKLLSLPAELSQLSRLSVLDVGSNQLKYNISNYHYDWNWRN 1100
1101 NKDLKYLNFSGNKRFEIKSALDPEGKNDLSDLGILKQLRVLGLMDVTLKT 1150
1151 SKVPDESVSIRLRTTASMINGMRYGVADTLGQSDSVCSRDVTFERFRGRE 1200
1201 DECLICLYDGKNENASSGHKISKIIRDIYDKILIRLLEKYGEESDGIKRA 1250
1251 LRYSFLQLNKEINGMLVSVEDGNTDSGLTSADLLSGSSATVVYLKGKKIY 1300
1301 TANIGDTMAVLSKNNGDFVTLTKLHVPAEREEYERIRTSGGYVNNQKLDG 1350
1351 VSEVSRAVGFFDLLPHIHASPDISETVLSYSDEMLIIATHKLWEYLDYET 1400
1401 VCDISRENKSQPMSAAEKMKDYAISYGCSDNITILCVSLDKSVNQQSQFT 1450
1451 LNREDLISRKNTFEDTVLRRLQPEIAPPTGNVAIVFTDIKNSTFLWELFP 1500
1501 DAMRAAIKTHNDIMRRQLRIYGGYEVKTEGDAFMVAFPTPTSALVWCLSV 1550
1551 QLKLLEAEWPEEITSIQDGCLITDNSGTKVYLGLSVRMGVHWGCPVPEID 1600
1601 LVTQRMDYLGPVVNKAARVSGVADGGQITLSSDFCSEFKKIMKFHKRVVE 1650
1651 NQEPLKEVYGEDFIGEVLEREIHMLENVGWVFKDLGEQKLKGLETKEFIT 1700
1701 IAYPKTLASRHDLATKNQNSSVLNDDLLFQLRTISNKLENILSSINGGLI 1750
1751 ESETPGNSSIYMTFDKNTKDAVITKSTESDWISFLDHLVTRVESTVAILQ 1800
1801 LRQKLQGGLELYTSSDSTMHKSVFELLDEILKIQTDQKQ 1839
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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