 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P11799 from www.uniprot.org...
The NucPred score for your sequence is 0.70 (see score help below)
1 MGDVKLVTSTRVSKTSLTLSPSVPAEAPAFTLPPRNIRVQLGATARFEGK 50
51 VRGYPEPQITWYRNGHPLPEGDHYVVDHSIRGIFSLVIKGVQEGDSGKYT 100
101 CEAANDGGVRQVTVELTVEGNSLKKYSLPSSAKTPGGRLSVPPVEHRPSI 150
151 WGESPPKFATKPNRVVVREGQTGRFSCKITGRPQPQVTWTKGDIHLQQNE 200
201 RFNMFEKTGIQYLEIQNVQLADAGIYTCTVVNSAGKASVSAELTVQGPDK 250
251 TDTHAQPLCMPPKPTTLATKAIENSDFKQATSNGIAKELKSTSTELMVET 300
301 KDRLSAKKETFYTSREAKDGKQGQNQEANAVPLQESRGTKGPQVLQKTSS 350
351 TITLQAVKAQPEPKAEPQTTFIRQAEDRKRTVQPLMTTTTQENPSLTGQV 400
401 SPRSRETENRAGVRKSVKEEKREPLGIPPQFESRPQSLEASEGQEIKFKS 450
451 KVSGKPKPDVEWFKEGVPIKTGEGIQIYEEDGTHCLWLKKACLGDSGSYS 500
501 CAAFNPRGQTSTSWLLTVKRPKVEEVAPCFSSVLKGCTVSEGQDFVLQCY 550
551 VGGVPVPEITWLLNEQPIQYAHSTFEAGVAKLTVQDALPEDDGIYTCLAE 600
601 NNAGRASCSAQVTVKEKKSSKKAEGTQAAKLNKTFAPIFLKGLTDLKVMD 650
651 GSQVIMTVEVSANPCPEIIWLHNGKEIQETEDFHFEKKGNEYSLYIQEVF 700
701 PEDTGKYTCEAWNELGETQTQATLTVQEPQDGIQPWFISKPRSVTAAAGQ 750
751 NVLISCAIAGDPFPTVHWFKDGQEITPGTGCEILQNEDIFTLILRNVQSR 800
801 HAGQYEIQLRNQVGECSCQVSLMLRESSASRAEMLRDGRESASSGERRDG 850
851 GNYGALTFGRTSGFKKSSSETRAAEEEQEDVRGVLKRRVETREHTEESLR 900
901 QQEAEQLDFRDILGKKVSTKSFSEEDLKEIPAEQMDFRANLQRQVKPKTL 950
951 SEEERKVHAPQQVDFRSVLAKKGTPKTPLPEKVPPPKPAVTDFRSVLGAK 1000
1001 KKPPAENGSASTPAPNARAGSEAQNATPNSEAPAPKPVVKKEEKNDRKCE 1050
1051 HGCAVVDGGIIGKKAENKPAASKPTPPPSKGTAPSFTEKLQDAKVADGEK 1100
1101 LVLQCRISSDPPASVSWTLDSKAIKSSKSIVISQEGTLCSLTIEKVMPED 1150
1151 GGEYKCIAENAAGKAECACKVLVEDTSSTKAAKPAEKKTKKPKTTLPPVL 1200
1201 STESSEATVKKKPAPKTPPKAATPPQITQFPEDRKVRAGESVELFAKVVG 1250
1251 TAPITCTWMKFRKQIQENEYIKIENAENSSKLTISSTKQEHCGCYTLVVE 1300
1301 NKLGSRQAQVNLTVVDKPDPPAGTPCASDIRSSSLTLSWYGSSYDGGSAV 1350
1351 QSYTVEIWNSVDNKWTDLTTCRSTSFNVQDLQADREYKFRVRAANVYGIS 1400
1401 EPSQESEVVKVGEKQEEELKEEEAELSDDEGKETEVNYRTVTINTEQKVS 1450
1451 DVYNIEERLGSGKFGQVFRLVEKKTGKVWAGKFFKAYSAKEKENIRDEIS 1500
1501 IMNCLHHPKLVQCVDAFEEKANIVMVLEMVSGGELFERIIDEDFELTERE 1550
1551 CIKYMRQISEGVEYIHKQGIVHLDLKPENIMCVNKTGTSIKLIDFGLARR 1600
1601 LESAGSLKVLFGTPEFVAPEVINYEPIGYETDMWSIGVICYILVSGLSPF 1650
1651 MGDNDNETLANVTSATWDFDDEAFDEISDDAKDFISNLLKKDMKSRLNCT 1700
1701 QCLQHPWLQKDTKNMEAKKLSKDRMKKYMARRKWQKTGHAVRAIGRLSSM 1750
1751 AMISGMSGRKASGSSPTSPINADKVENEDAFLEEVAEEKPHVKPYFTKTI 1800
1801 LDMEVVEGSAARFDCKIEGYPDPEVMWYKDDQPVKESRHFQIDYDEEGNC 1850
1851 SLTISEVCGDDDAKYTCKAVNSLGEATCTAELLVETMGKEGEGEGEGEED 1900
1901 EEEEEE 1906
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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