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Calculated ChIP intervals were visualized with IGB software [ 42].
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We divided each chromosome into 10-kb nonoverlapping windows and calculated ChIP-seq read enrichment within each window.
We calculated chip-chip correlation in each region by using RMA summaries values and defined blocks by visual inspection of the correlation heatmaps.
To calculate ChIP enrichment/input, ΔCT was calculated according to: ΔCT = (CT(ChIP) − [CT(Input)− logE (Input dilution factor)]) where E represents the specific primer efficiency value.
Additionally, we estimate the polygenetic effects of expression regulation by calculating chip-wise (CW) heritability (29).
We calculated the ChIP signal for each subpeak at each stage by summing the ChIP signal around a 500 bp window center around of each peak position in the normalized ChIP profile generated as described above.
We then calculated normalized ChIP-Seq signal intensities on each window as RPM difference between ChIP and input DNA control data (RPMChIP – RPMinput).
As probe weights for signal summary statistic calculation, we used the inverse of the probe-specific coefficient of variation calculated across chips.
Due to the different length scales presented in this problem, a small-scale model was developed using a simple thermal resistance formulation for the chips, in order to calculate the chip junction temperature at different operating conditions.
The interfacial fracture energy was calculated for chipping mechanism of FeB.
Profiles around each of the 179 369 globally defined RTSSs in each cell line for all chromatin marks were calculated from ChIP-Seq mapped sequence read libraries downloaded from ENCODE.
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