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MACS (Model-based Analysis of ChIP-Seq) is another algorithm besides QuEST that takes advantage of the observed bimodal enrichment patterns of binding sites by empirically modelling the shift size.
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Moreover, it is able to model the shift size of the tags using the strand information from the most enriched genomic regions, defined through the mfold parameter.
QR methods offer the most robust approach to flexibly model the shifts in HAZ distribution associated with changes to covariates.
MACS software takes advantage of this bimodal pattern to empirically model the shifting size to better locate the precise binding sites.
We simulated trees with different values of λ, μ and species number to model the lineage shifts in diversification rates.
For the crash model the mean shift is located at July 1978, whereas for the mixed change model the shift in mean and slope appears located at April 1979.
Using these models, the shift of bearing eigenfrequencies as a result of lubrication is investigated and modal damping values for the preloaded bearing are estimated.
In the 1 D extended model, the shift of the auxin maximum may be compensated by increasing the number of cells in the array so that the auxin maximum position maintains.
The algorithm empirically models the shift size of sequence reads, and employs a Poisson distribution as a background model to capture local biases attributed to inherent differential sequencing and mapping genomic properties.
MACS (Model-based Analysis of ChIP-Seq) [ 24] empirically models the shift size of ChIP-seq tags to enhance peak identification by taking advantage of the bimodal pattern of forward and reverse tags.
For model D, the shift of Fano antiresonances exhibits different results.
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