 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P41647 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MIKVLGLLLGPLSSWVEVSGPIIIFGLYYGFLATLPFGPSKIYSTRSFLL 50
51 GKPGYGIIAISGSITGQLIGFLSMYYSPIYAALWKPYAITLLVVPYMFFR 100
101 FFQIMDKPSSSESPHLMNSINNPKALSLFMDGLILQLLNPILLANPVLTR 150
151 LVNLFLFRYSPNISFMISGLCGWLGGHILLTIFIKWVSFRIDRNSLIDNT 200
201 LLRRYINRTFSLLILCYCSFYLGRAPLPFLKGKNYEDNNGRSVTMARDDR 250
251 SVAMARKNRSVAIDPQKLQELIKEEKFFRQQPWPIMCFDHNRVYQPIRYI 300
301 GNSPFTRLGPVRTEVSQYFFGAYSSDGKKRISFTFLPSVLVLGEKLVGGY 350
351 RDFLYTSCSSEDPYYRWNHTVKRKRDSLGNEFSDRVKALSHGSPAENVIE 400
401 RRVKFSNSNGDSFTEMYDPFLNGAFRGTINQFESPQMLNDSIISNLSDFI 450
451 EIFMRDPKEGFPNDPLGYGYHISYLWQELEHESFPLPWEPLPTYTVRSLV 500
501 PVTISSNPGTPQPKYALNRLKMKKISYLIQTPEIQPPYWLWIAWRSSIIH 550
551 VPVQVARCYGDIYTNFLVYVYGRFDRLIKPSASGIIRMDAISCLFKKEYL 600
601 FVYENLCFLFECLAQYEWTILLISRAGIPRDKRYSMEKKDFISLYREILL 650
651 NEPLQIREIRKHVPRWSSGLMIGEYDDVDPVLLSSNRILSRKVKDTMTFD 700
701 IGQRRIGVVQNRYSAEADYRRNLIQGSIRAKRRKIMIWKRIQPNVHSLFF 750
751 LKRKEIPAYPKDYYDTSDSGRVDKEQIGEEVREKIQRVEDPLSQQTIAES 800
801 LCLTWPELHYFRGLLLMAQSNIRKNIILPSLIIAKNMGRILLFQVPEFYK 850
851 DWEEMRREMHVICASDGTELSETTFPDKWETQGMQIKLLFPFRLKPWHRS 900
901 KPQSAKRLRWSYLTTFGLETDIPFGDPTSNLGIFSKFLKPIFKKVKRRLM 950
951 GSTGIRRVPRVGYIDKSELNDRIQNKLLSETTPMGSANDSSEVNDQFGYE 1000
1001 TQTINVKDQDDWTTTMKERIESIAIINSSPITGMSLVDSEIHTGSKGSFN 1050
1051 ILGSTLKKRLVQIRRIPGLFRNKSVQLIRKRFYSIKFFIKRMDRRMDRDL 1100
1101 LPSFINFIASNIKFWIQSAWIRSTRNITTIYGRIFIINKDISRINRGKIT 1150
1151 NYYSINEKIQDFEIRPDRNMFSMSQAYIFHKIWQIRALDIQRILDHEKPQ 1200
1201 DLKENDWKQWLRCFDRYNLSPQIWSRINPNKCRNIVNKQCTCYEERFVPY 1250
1251 EQQEDSIFATVMEPFLGLLRKMNKRYRYDLLSYSYLNSTKDLDILNLTDI 1300
1301 PGPPVQPAIPDERDITDREGILKEKFINDIIEEDWKGTDFNIVNGSRSTV 1350
1351 DIYDAIRSCDYDHTTSIDRQKKKTDLITNQQGIDETRRENVGIMDSPKIE 1400
1401 KRISQLDLNFWLFPELSGIKNIYYETKSKFIPGNSLLREERERKKIEEEE 1450
1451 RKETTNVLEQIIGIRSNVKNKQVEDGQDKNGQVEDQDGQDQDGQVEDQQT 1500
1501 DGKKKTNKGLFQCKVVDVLGKKRFFYLANICRVMSGMKDPGTYLRIQERN 1550
1551 IDLSLMAFCIAIQKNSSANKISKELALQRNVRGKVRNDNEIREDKKIMVF 1600
1601 QPYRLSSIVDDQFLMYKIVSISLKLKKRAGEWIDGDFYDGSVQRGKILGD 1650
1651 EKNIFSSLNLEDILLPKRRREFRILNRFDLENDHVGFSNGKDIQNDEELM 1700
1701 GRDQHLSVDTTQIIKRFLWPSYRLEDIICMNRYWFNTNDGSRSAMLRIRM 1750
1751 YPLTVN 1756
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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