 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6WKZ8 from www.uniprot.org...
The NucPred score for your sequence is 0.90 (see score help below)
1 MASEMEPEVQAIDRSLLECSAEEIAGRWLQATDLNREVYQHLAHCVPKIY 50
51 CRGPNPFPQKEDTLAQHILLGPMEWYICAEDPALGFPKLEQANKPSHLCG 100
101 RVFKVGEPTYSCRDCAVDPTCVLCMECFLGSIHRDHRYRMTTSGGGGFCD 150
151 CGDTEAWKEGPYCQKHKLSSSEVVEEEDPLVHLSEDVIARTYNIFAIMFR 200
201 YAVDILTWEKESELPEDLEVAEKSDTYYCMLFNDEVHTYEQVIYTLQKAV 250
251 NCTQKEAIGFATTVDRDGRRSVRYGDFQYCDQAKTVIVRNTSRQTKPLKV 300
301 QVMHSSVAAHQNFGLKALSWLGSVIGYSDGLRRILCQVGLQEGPDGENSS 350
351 LVDRLMLNDSKLWKGARSVYHQLFMSSLLMDLKYKKLFALRFAKNYRQLQ 400
401 RDFMEDDHERAVSVTALSVQFFTAPTLARMLLTEENLMTVIIKAFMDHLK 450
451 HRDAQGRFQFERYTALQAFKFRRVQSLILDLKYVLISKPTEWSDELRQKF 500
501 LQGFDAFLELLKCMQGMDPITRQVGQHIEMEPEWEAAFTLQMKLTHVISM 550
551 VQDWCALDEKVLIEAYKKCLAVLTQCHGGFTDGEQPITLSICGHSVETIR 600
601 YCVSQEKVSIHLPISRLLAGLHVLLSKSEVAYKFPELLPLSELSPPMLIE 650
651 HPLRCLVLCAQVHAGMWRRNGFSLVNQIYYYHNVKCRREMFDKDIVMLQT 700
701 GVSMMDPNHFLMIMLSRFELYQLFSTPDYGKRFSSEVTHKDVVQQNNTLI 750
751 EEMLYLIIMLVGERFNPGVGQVAATDEIKREIIHQLSIKPMAHSELVKSL 800
801 PEDENKETGMESVIESVAHFKKPGLTGRGMYELKPECAKEFNLYFYHFSR 850
851 AEQSKAEEAQRKLKRENKEDTALPPPALPPFCPLFASLVNILQCDVMLYI 900
901 MGTILQWAVEHHGSAWSESMLQRVLHLIGMALQEEKHHLENAVEGHVQTF 950
951 TFTQKISKPGDAPHNSPSILAMLETLQNAPSLEAHKDMIRWLLKMFNAIK 1000
1001 KIRECSSSSPVAEAEGTIMEESSRDKDKAERKRKAEIARLRREKIMAQMS 1050
1051 EMQRHFIDENKELFQQTLELDTSASATLDSSPPVSDAALTALGPAQTQVP 1100
1101 EPRQFVTCILCQEEQEVTVGSRAMVLAAFVQRSTVLSKDRTKTIADPEKY 1150
1151 DPLFMHPDLSCGTHTGSCGHVMHAHCWQRYFDSVQAKEQRRQQRLRLHTS 1200
1201 YDVENGEFLCPLCECLSNTVIPLLLPPRSILSRRLNFSDQPDLAQWTRAV 1250
1251 TQQIKVVQMLRRKHNAADTSSSEDTEAMNIIPIPEGFRPDFYPRNPYSDS 1300
1301 IKEMLTTFGTAAYKVGLKVHPNEGDPRVPILCWGTCAYTIQSIERILSDE 1350
1351 EKPVFGPLPCRLDDCLRSLTRFAAAHWTVALLPVVQGHFCKLFASLVPSD 1400
1401 SYEDLPCILDIDMFHLLVGLVLAFPALQCQDFSGSSLATGDLHIFHLVTM 1450
1451 AHIVQILLTSCTEENGMDQENPTGEEELAILSLHKTLHQYTGSALKEAPS 1500
1501 GWHLWRSVRAAIMPFLKCSALFFHYLNGVPAPPDLQVSGTSHFEHLCNYL 1550
1551 SLPTNLIHLFQENSDIMNSLIESWCQNSEVKRYLNGERGAISYPRGANKL 1600
1601 IDLPEDYSSLINQASNFSCPKSGGDKSRAPTLCLVCGSLLCSQSYCCQAE 1650
1651 LEGEDVGACTAHTYSCGSGAGIFLRVRECQVLFLAGKTKGCFYSPPYLDD 1700
1701 YGETDQGLRRGNPLHLCQERFRKIQKLWQQHSITEEIGHAQEANQTLVGI 1750
1751 DWQHL 1755
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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