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It ranks the candidate control genes by estimating their expression stability while also taking into account the experimental design (control and disease groups).
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In brief, the algorithm first distinguishes candidate interactions between a TF and its targets by estimating the expression pairwise mutual information (MI).
This was achieved first by estimating the expression level of each isoform contained in Ensembl database by cufflinks software version 2.0.2 (Trapnell et al., 2010) with following parameters: -G Mus_musculus.GRCm38.68.gtf -u -j 0.8 -m 160 -s 50 -N.
Apoptosis in the cavernosal tissues of Mn-treated mice was further assessed by estimating the expression levels of caspase-12 and caspase-3, two important activators for apoptosis signaling.
We identified a weighted gene co-expression network in MI by estimating similar gene expression patterns across mice-derived samples.
Subsequently we used this to define, transcriptomic brain networks by estimating gene co-expression between pairs of cortical regions.
BestKeeper allows a comparative analysis across internal reference genes by estimating correlations in the expression levels between all the possible candidates.
We adjusted this baseline difference by estimating the difference between the expression levels of housekeeping genes common to the two datasets.
A more recent method handles isoform multireads by explicitly estimating isoform expression levels but does not handle gene multireads (Jiang and Wong, 2009).
Osteoblast differentiation was quantified by estimating the accumulation of mineralized matrix and expression of osteogenic genes.
p63 protein expression was scored by estimating the percentage of positive nuclei in tumor cells.
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