 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P15146 from www.uniprot.org...
The NucPred score for your sequence is 0.85 (see score help below)
1 MADERKDEGKAPHWTSASLTEAAAHPHSPEMKDQGGSGEGLSRSANGFPY 50
51 REEEEGAFGEHGSQGTYSDTKENGINGELTSADRETAEEVSARIVQVVTA 100
101 EAVAVLKGEQEKEAQHKDQPAALPLAAEETVNLPPSPPPSPASEQTAALE 150
151 EDLLTASKMEFPEQQKLPSSFAEPLDKEETEFKMQSKPGEDFEHAALVPQ 200
201 PDTSKTPQDKKDPQDMEGEKSPASPFAQTFGTNLEDIKQITEPSITVPSI 250
251 GLSAEPLAPKDQKDWFIEMPVESKKDEWGLAAPISPGPLTPMREKDVLED 300
301 IPRWEGKQFDSPMPSPFHGGSFTLPLDTVKDERVTEGSQPFAPVFFQSDD 350
351 KMSLQDTSGSATSKESSKDEEPQKDKADKVADVPVSEATTVLGDVHSPAV 400
401 EGFVGENISGEEKGTTDQEKKETSTPSVQEPTLTETEPQTKLEETSKVSI 450
451 EETVAKEEESLKLKDDKAGVIQTSTEQSFSKEDQKGQEQTIEALKQDSFP 500
501 ISLEQAVTDAAMATKTLEKVTSEPEAVSEKREIQGLFEEDIADKSKLEGA 550
551 GSATVAEVEMPFYEDKSGMSKYFETSALKEDVTRSTGLGSDYYELSDSRG 600
601 NAQESLDTVSPKNQQDEKELLAKASQPSPPAHEAGYSTLAQSYTSDHPSE 650
651 LPEEPSSPQERMFTIDPKVYGEKRDLHSKNKDDLTLSRSLGLGGRSAIEQ 700
701 RSMSINLPMSCLDSIALGFNFGRGHDLSPLASDILTNTSGSMDEGDDYLP 750
751 PTTPAVEKIPCFPIESKEEEDKTEQAKVTGGQTTQVETSSESPFPAKEYY 800
801 KNGTVMAPDLPEMLDLAGTRSRLASVSADAEVARRKSVPSEAVVAESSTG 850
851 LPPVADDSQPVKPDSQLEDMGYCVFNKYTVPLPSPVQDSENLSGESGSFY 900
901 EGTDDKVRRDLATDLSLIEVKLAAAGRVKDEFTAEKEASPPSSADKSGLS 950
951 REFDQDRKANDKLDTVLEKSEEHVDSKEHAKESEEVGDKVELFGLGVTYE 1000
1001 QTSAKELITTKETAPERAEKGLSSVPEVAEVETTTKADQGLDVAAKKDDQ 1050
1051 SPLDIKVSDFGQMASGMSVDAGKTIELKFEVDQQLTLSSEAPQETDSFMG 1100
1101 IESSHVKDGAKVSETEVKEKVAKPDLVHQEAVDKEESYESSGEHESLTME 1150
1151 SLKPDEGKKETSPETSLIQDEVALKLSVEIPCPPPVSEADSSIDEKAEVQ 1200
1201 MEFIQLPKEESTETPDIPAIPSDVTQPQPEAVVSEPAEVRGEEEEIEAEG 1250
1251 EYDKLLFRSDTLQITDLLVPGSREEFVETCPGEHKGVVESVVTIEDDFIT 1300
1301 VVQTTTDEGELGSHSVRFAAPVQPEEERRPYPHDEELEVLMAAEAQAEPK 1350
1351 DGSPDAPATPEKEEVPFSEYKTETYDDYKDETTIDDSIMDADSLWVDTQD 1400
1401 DDRSILTEQLETIPKEERAEKEARRPSLEKHRKEKPFKTGRGRISTPERR 1450
1451 EVAKKEPSTVSRDEVRRKKAVYKKAELAKESEVQAHSPSRKLILKPAIKY 1500
1501 TRPTHLSCVKRKTTATSGESAQAPSAFKQAKDKVTDGITKSPEKRSSLPR 1550
1551 PSSILPPRRGVSGDREENSFSLNSSISSARRTTRSEPIRRAGKSGTSTPT 1600
1601 TPGSTAITPGTPPSYSSRTPGTPGTPSYPRTPGTPKSGILVPSEKKVAII 1650
1651 RTPPKSPATPKQLRLINQPLPDLKNVKSKIGSTDNIKYQPKGGQVRILNK 1700
1701 KMDFSKVQSRCGSKDNIKHSAGGGNVQIVTKKIDLSHVTSKCGSLKNIRH 1750
1751 RPGGGRVKIESVKLDFKEKAQAKVGSLDNAHHVPGGGNVKIDSQKLNFRE 1800
1801 HAKARVDHGAEIITQSPSRSSVASPRRLSNVSSSGSINLLESPQLATLAE 1850
1851 DVTAALAKQGL 1861
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.) |
Go back to the NucPred Home Page.