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A statistical approach, named Naïve Bayesian Network, integrated such disperse genomic-scale predictors and gained a more comprehensive and reliable set of core mitochondrial proteins, named CoreMitoP, by joining experimentally verified ones and excluding false predicted ones.
Moreover, by joining experimentally verified ones with ArathMitoP and excluding false positives, we got a set of 2,585 nonredundant mitochondrial proteins, named CoreMitoP, including 456 proteins identified by mass spectrometry and 615 overlapped proteins from four bioinformatical predictors (s1, s2, s3, and s5) (Data S4).
Given that the estimated range of hinge loops agrees well with the semi-manually verified ones reported in [2] (Table 4), and the over extension is well prevented (as also shown in the Table S4), we conclude that the proposed procedure is a fully automated, precise, and generally applicable method for hinge loop detection.
To obtain a more reliable set of protein interactions, we excluded all the interactions obtained by homology methods: only experimentally verified ones were included in our analysis.
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Through bioinformatics screening and luciferase assay, we searched and verified one target gene of miR-29a DCX. miR-29a DCX
All articles "hits" were then verified, one at a time, that the species was harvested within the Northern African geographical regions.
While simple techniques such as windowing can be devised to tackle smaller time intervals where stationarity is (almost) verified, one would still need to find a way to integrate the information from different intervals.
We have experimentally verified one of the new gene model predictions to validate our results.
Unless experimentally verified, one can only say it is most likely to be inactive.
SJ coded the transcripts and CvE and LH each verified one-third of the transcripts as an inter-rater check.
In each step, the presence of at least four adenines in the window is verified (one base serves as a margin for sequencing errors).
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