 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q13332 from www.uniprot.org...
The NucPred score for your sequence is 0.51 (see score help below)
1 MAPTWGPGMVSVVGPMGLLVVLLVGGCAAEEPPRFIKEPKDQIGVSGGVA 50
51 SFVCQATGDPKPRVTWNKKGKKVNSQRFETIEFDESAGAVLRIQPLRTPR 100
101 DENVYECVAQNSVGEITVHAKLTVLREDQLPSGFPNIDMGPQLKVVERTR 150
151 TATMLCAASGNPDPEITWFKDFLPVDPSASNGRIKQLRSETFESTPIRGA 200
201 LQIESSEETDQGKYECVATNSAGVRYSSPANLYVRELREVRRVAPRFSIL 250
251 PMSHEIMPGGNVNITCVAVGSPMPYVKWMQGAEDLTPEDDMPVGRNVLEL 300
301 TDVKDSANYTCVAMSSLGVIEAVAQITVKSLPKAPGTPMVTENTATSITI 350
351 TWDSGNPDPVSYYVIEYKSKSQDGPYQIKEDITTTRYSIGGLSPNSEYEI 400
401 WVSAVNSIGQGPPSESVVTRTGEQAPASAPRNVQARMLSATTMIVQWEEP 450
451 VEPNGLIRGYRVYYTMEPEHPVGNWQKHNVDDSLLTTVGSLLEDETYTVR 500
501 VLAFTSVGDGPLSDPIQVKTQQGVPGQPMNLRAEARSETSITLSWSPPRQ 550
551 ESIIKYELLFREGDHGREVGRTFDPTTSYVVEDLKPNTEYAFRLAARSPQ 600
601 GLGAFTPVVRQRTLQSKPSAPPQDVKCVSVRSTAILVSWRPPPPETHNGA 650
651 LVGYSVRYRPLGSEDPEPKEVNGIPPTTTQILLEALEKWTQYRITTVAHT 700
701 EVGPGPESSPVVVRTDEDVPSAPPRKVEAEALNATAIRVLWRSPAPGRQH 750
751 GQIRGYQVHYVRMEGAEARGPPRIKDVMLADAQWETDDTAEYEMVITNLQ 800
801 PETAYSITVAAYTMKGDGARSKPKVVVTKGAVLGRPTLSVQQTPEGSLLA 850
851 RWEPPAGTAEDQVLGYRLQFGREDSTPLATLEFPPSEDRYTASGVHKGAT 900
901 YVFRLAARSRGGLGEEAAEVLSIPEDTPRGHPQILEAAGNASAGTVLLRW 950
951 LPPVPAERNGAIVKYTVAVREAGALGPARETELPAAAEPGAENALTLQGL 1000
1001 KPDTAYDLQVRAHTRRGPGPFSPPVRYRTFLRDQVSPKNFKVKMIMKTSV 1050
1051 LLSWEFPDNYNSPTPYKIQYNGLTLDVDGRTTKKLITHLKPHTFYNFVLT 1100
1101 NRGSSLGGLQQTVTAWTAFNLLNGKPSVAPKPDADGFIMVYLPDGQSPVP 1150
1151 VQSYFIVMVPLRKSRGGQFLTPLGSPEDMDLEELIQDISRLQRRSLRHSR 1200
1201 QLEVPRPYIAARFSVLPPTFHPGDQKQYGGFDNRGLEPGHRYVLFVLAVL 1250
1251 QKSEPTFAASPFSDPFQLDNPDPQPIVDGEEGLIWVIGPVLAVVFIICIV 1300
1301 IAILLYKNKPDSKRKDSEPRTKCLLNNADLAPHHPKDPVEMRRINFQTPD 1350
1351 SGLRSPLREPGFHFESMLSHPPIPIADMAEHTERLKANDSLKLSQEYESI 1400
1401 DPGQQFTWEHSNLEVNKPKNRYANVIAYDHSRVILQPIEGIMGSDYINAN 1450
1451 YVDGYRCQNAYIATQGPLPETFGDFWRMVWEQRSATIVMMTRLEEKSRIK 1500
1501 CDQYWPNRGTETYGFIQVTLLDTIELATFCVRTFSLHKNGSSEKREVRQF 1550
1551 QFTAWPDHGVPEYPTPFLAFLRRVKTCNPPDAGPIVVHCSAGVGRTGCFI 1600
1601 VIDAMLERIKPEKTVDVYGHVTLMRSQRNYMVQTEDQYSFIHEALLEAVG 1650
1651 CGNTEVPARSLYAYIQKLAQVEPGEHVTGMELEFKRLANSKAHTSRFISA 1700
1701 NLPCNKFKNRLVNIMPYESTRVCLQPIRGVEGSDYINASFIDGYRQQKAY 1750
1751 IATQGPLAETTEDFWRMLWENNSTIVVMLTKLREMGREKCHQYWPAERSA 1800
1801 RYQYFVVDPMAEYNMPQYILREFKVTDARDGQSRTVRQFQFTDWPEQGVP 1850
1851 KSGEGFIDFIGQVHKTKEQFGQDGPISVHCSAGVGRTGVFITLSIVLERM 1900
1901 RYEGVVDIFQTVKMLRTQRPAMVQTEDEYQFCYQAALEYLGSFDHYAT 1948
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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