 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q68FH0 from www.uniprot.org...
The NucPred score for your sequence is 0.87 (see score help below)
1 MPAPEQGSLVEEGQPQTHQEAVSTGPGMEPETTATTILASVKEQELQFQR 50
51 LTRELEVERQIVASQLERCRLGAESPSIASTSSTEKSFPWRSTDVPNPGV 100
101 SKPRVSDTIHPNNYLIRTEPEQGTLYSPEQTSLHESEGSLGNSRSSTQMN 150
151 SYSDSGYQEAGSFHNSQTVNKADSRQHPFTGSTSNHVVRTSRAEGQTLVQ 200
201 PSVANRAMRRVSSVPSRAQSPSYVTSTGVSPSRGSLRTSLGSGFGSPSVT 250
251 DSRPLNPSAYSSSTLPAQRAASPYSQRPASPTAVRRVGSVTSRQTSNPNG 300
301 PVPQYQTTTRVGSPLTLTDAQTRVASPSQGQVGSSSPKRSGMTAVPQHLG 350
351 PSLQRTVHDMDQFGQQQYDIYERMVPPRPDSLTGLRSSYASQHSQLGQEL 400
401 RSAVSPDLHITPIYEGRTYYSPVYRSPNHGTVELQGSQTALYRTGSVGIG 450
451 NLQRTSSQRSTLTYQRNNYALNTAATYAEPYRPVQYRVQECSYNRLQHTG 500
501 PADDGATRSPSIDSIQKDPREFAWRDPELPEVIHMLQHQFPSVQANAAAY 550
551 LQHLCFGDNKVKMEVYRLGGIKHLVDLLDHRVLEVQKNACGALRNLVFGK 600
601 STDENKIAMKNVGGIPALLRLLRKSIDAEVRELVTGVLWNLSSCDAVKMT 650
651 IIRDALSTLTNTVIVPHSGWNNSSFDDDHKIKFQTSLVLRNTTGCLRNLS 700
701 SAGEEARKQMRSCEGLVDSLLYVIHTCVNTSDYDSKTVENCVCTLRNLSY 750
751 RLELEVPQARLLGLNELDDLLGKESPSKDSEPSCWGKKKKKKKRTPQEDQ 800
801 WDGVGPIPGLSKSPKGVEMLWHPSVVKPYLTLLAESSNPATLEGSAGSLQ 850
851 NLSAGNWKFAAYIRAAVRKEKGLPILVELLRMDNDRVVSSVATALRNMAL 900
901 DVRNKELIGKYAMRDLVNRLPGGNGPSILSDETVAAICCALHEVTSKNME 950
951 NAKALADSGGIEKLVNITKGRGDRSSLKVVKAAAQVLNTLWQYRDLRSIY 1000
1001 KKDGWNQNHFITPVSTLERDRFKSHPSLSTTNQQMSPIIQSVGSTSSSPA 1050
1051 LLGIREPRSEYDRTQPPMQYYNSQGDTTHKGLYPGSSKPSPIYISSYSSP 1100
1101 AREQNRRLQHQQLYYQDDSTRKTLDAYRLYLQSPRSYEDPYCDDRVHFPA 1150
1151 STDYSTQYGLKSTTNYVDFYSTKRPSYRAEQYPGSPDSWV 1190
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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