 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O60346 from www.uniprot.org...
The NucPred score for your sequence is 0.84 (see score help below)
1 MEPAAAATVQRLPELGREDRASAPAAAAAAAAAAAAAAAALAAAAGGGRS 50
51 PEPALTPAAPSGGNGSGSGAREEAPGEAPPGPLPGRAGGAGRRRRRGAPQ 100
101 PIAGGAAPVPGAGGGANSLLLRRGRLKRNLSAAAAAASSSSSSSAAAASH 150
151 SPGAAGLPASCSASASLCTRSLDRKTLLLKHRQTLQLQPSDRDWVRHQLQ 200
201 RGCVHVFDRHMASTYLRPVLCTLDTTAGEVAARLLQLGHKGGGVVKVLGQ 250
251 GPGAAAAREPAEPPPEAGPRLAPPEPRDSEVPPARSAPGAFGGPPRAPPA 300
301 DLPLPVGGPGGWSRRASPAPSDSSPGEPFVGGPVSSPRAPRPVVSDTESF 350
351 SLSPSAESVSDRLDPYSSGGGSSSSSEELEADAASAPTGVPGQPRRPGHP 400
401 AQPLPLPQTASSPQPQQKAPRAIDSPGGAVREGSCEEKAAAAVAPGGLQS 450
451 TPGRSGVTAEKAPPPPPPPTLYVQLHGETTRRLEAEEKPLQIQNDYLFQL 500
501 GFGELWRVQEEGMDSEIGCLIRFYAGKPHSTGSSERIQLSGMYNVRKGKM 550
551 QLPVNRWTRRQVILCGTCLIVSSVKDSLTGKMHVLPLIGGKVEEVKKHQH 600
601 CLAFSSSGPQSQTYYICFDTFTEYLRWLRQVSKVASQRISSVDLSCCSLE 650
651 HLPANLFYSQDLTHLNLKQNFLRQNPSLPAARGLNELQRFTKLKSLNLSN 700
701 NHLGDFPLAVCSIPTLAELNVSCNALRSVPAAVGVMHNLQTFLLDGNFLQ 750
751 SLPAELENMKQLSYLGLSFNEFTDIPEVLEKLTAVDKLCMSGNCVETLRL 800
801 QALRKMPHIKHVDLRLNVIRKLIADEVDFLQHVTQLDLRDNKLGDLDAMI 850
851 FNNIEVLHCERNQLVTLDICGYFLKALYASSNELVQLDVYPVPNYLSYMD 900
901 VSRNRLENVPEWVCESRKLEVLDIGHNQICELPARLFCNSSLRKLLAGHN 950
951 QLARLPERLERTSVEVLDVQHNQLLELPPNLLMKADSLRFLNASANKLES 1000
1001 LPPATLSEETNSILQELYLTNNSLTDKCVPLLTGHPHLKILHMAYNRLQS 1050
1051 FPASKMAKLEELEEIDLSGNKLKAIPTTIMNCRRMHTVIAHSNCIEVFPE 1100
1101 VMQLPEIKCVDLSCNELSEVTLPENLPPKLQELDLTGNPRLVLDHKTLEL 1150
1151 LNNIRCFKIDQPSTGDASGAPAVWSHGYTEASGVKNKLCVAALSVNNFCD 1200
1201 NREALYGVFDGDRNVEVPYLLQCTMSDILAEELQKTKNEEEYMVNTFIVM 1250
1251 QRKLGTAGQKLGGAAVLCHIKHDPVDPGGSFTLTSANVGKCQTVLCRNGK 1300
1301 PLPLSRSYIMSCEEELKRIKQHKAIITEDGKVNGVTESTRILGYTFLHPS 1350
1351 VVPRPHVQSVLLTPQDEFFILGSKGLWDSLSVEEAVEAVRNVPDALAAAK 1400
1401 KLCTLAQSYGCHDSISAVVVQLSVTEDSFCCCELSAGGAVPPPSPGIFPP 1450
1451 SVNMVIKDRPSDGLGVPSSSSGMASEISSELSTSEMSSEVGSTASDEPPP 1500
1501 GALSENSPAYPSEQRCMLHPICLSNSFQRQLSSATFSSAFSDNGLDSDDE 1550
1551 EPIEGVFTNGSRVEVEVDIHCSRAKEKEKQQHLLQVPAEASDEGIVISAN 1600
1601 EDEPGLPRKADFSAVGTIGRRRANGSVAPQERSHNVIEVATDAPLRKPGG 1650
1651 YFAAPAQPDPDDQFIIPPELEEEVKEIMKHHQEQQQQQQPPPPPQLQPQL 1700
1701 PRHYQLDQLPDYYDTPL 1717
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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