 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P36594 from www.uniprot.org...
The NucPred score for your sequence is 0.59 (see score help below)
1 MSGIQFSPSSVPLRRVEEVQFGILSPEEIRSMSVAKIEFPETMDESGQRP 50
51 RVGGLLDPRLGTIDRQFKCQTCGETMADCPGHFGHIELAKPVFHIGFLSK 100
101 IKKILECVCWNCGKLKIDSSNPKFNDTQRYRDPKNRLNAVWNVCKTKMVC 150
151 DTGLSAGSDNFDLSNPSANMGHGGCGAAQPTIRKDGLRLWGSWKRGKDES 200
201 DLPEKRLLSPLEVHTIFTHISSEDLAHLGLNEQYARPDWMIITVLPVPPP 250
251 SVRPSISVDGTSRGEDDLTHKLSDIIKANANVRRCEQEGAPAHIVSEYEQ 300
301 LLQFHVATYMDNEIAGQPQALQKSGRPLKSIRARLKGKEGRLRGNLMGKR 350
351 VDFSARTVITGDPNLSLDELGVPRSIAKTLTYPETVTPYNIYQLQELVRN 400
401 GPDEHPGAKYIIRDTGERIDLRYHKRAGDIPLRYGWRVERHIRDGDVVIF 450
451 NRQPSLHKMSMMGHRIRVMPYSTFRLNLSVTSPYNADFDGDEMNMHVPQS 500
501 EETRAEIQEITMVPKQIVSPQSNKPVMGIVQDTLAGVRKFSLRDNFLTRN 550
551 AVMNIMLWVPDWDGILPPPVILKPKVLWTGKQILSLIIPKGINLIRDDDK 600
601 QSLSNPTDSGMLIENGEIIYGVVDKKTVGASQGGLVHTIWKEKGPEICKG 650
651 FFNGIQRVVNYWLLHNGFSIGIGDTIADADTMKEVTRTVKEARRQVAECI 700
701 QDAQHNRLKPEPGMTLRESFEAKVSRILNQARDNAGRSAEHSLKDSNNVK 750
751 QMVAAGSKGSFINISQMSACVGQQIVEGKRIPFGFKYRTLPHFPKDDDSP 800
801 ESRGFIENSYLRGLTPQEFFFHAMAGREGLIDTAVKTAETGYIQRRLVKA 850
851 MEDVMVRYDGTVRNAMGDIIQFAYGEDGLDATLVEYQVFDSLRLSTKQFE 900
901 KKYRIDLMEDRSLSLYMENSIENDSSVQDLLDEEYTQLVADRELLCKFIF 950
951 PKGDARWPLPVNVQRIIQNALQIFHLEAKKPTDLLPSDIINGLNELIAKL 1000
1001 TIFRGSDRITRDVQNNATLLFQILLRSKFAVKRVIMEYRLNKVAFEWIMG 1050
1051 EVEARFQQAVVSPGEMVGTLAAQSIGEPATQMTLNTFHYAGVSSKNVTLG 1100
1101 VPRLKEILNVAKNIKTPSLTIYLMPWIAANMDLAKNVQTQIEHTTLSTVT 1150
1151 SATEIHYDPDPQDTVIEEDKDFVEAFFAIPDEEVEENLYKQSPWLLRLEL 1200
1201 DRAKMLDKKLSMSDVAGKIAESFERDLFTIWSEDNADKLIIRCRIIRDDD 1250
1251 RKAEDDDNMIEEDVFLKTIEGHMLESISLRGVPNITRVYMMEHKIVRQIE 1300
1301 DGTFERADEWVLETDGINLTEAMTVEGVDATRTYSNSFVEILQILGIEAT 1350
1351 RSALLKELRNVIEFDGSYVNYRHLALLCDVMTSRGHLMAITRHGINRAET 1400
1401 GALMRCSFEETVEILMDAAASGEKDDCKGISENIMLGQLAPMGTGAFDIY 1450
1451 LDQDMLMNYSLGTAVPTLAGSGMGTSQLPEGAGTPYERSPMVDSGFVGSP 1500
1501 DAAAFSPLVQGGSEGREGFGDYGLLGAASPYKGVQSPGYTSPFSSAMSPG 1550
1551 YGLTSPSYSPSSPGYSTSPAYMPSSPSYSPTSPSYSPTSPSYSPTSPSYS 1600
1601 PTSPSYSATSPSYSPTSPSYSPTSPSYSPTSPSYSPTSPSYSPTSPSYSP 1650
1651 TSPSYSPTSPSYSPTSPSYSPTSPSYSPTSPSYSPTSPSYSPTSPSYSPT 1700
1701 SPSYSPTSPSYSPTSPSYSPTSPSYSPTSPSYSPTSPSYSPTSPSYSPTS 1750
1751 PS 1752
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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