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The closeness measure is applied to genome-wide CpG methylation and histone modification datasets in human CD4+T cells to select a subset of potential features.
In addition, the histone modification datasets in H9 were generated by the Ren laboratory and released as part of the Roadmap Epigenome Project and can be accessed using GSE16256.
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This difference in H3K4me3 modification signature could be reproduced using other H3K4me3 modification datasets obtained from human and rhesus macaque PFC samples, as well as HeLa cells [ 39– 41] (Additional file 5: Figure S6).
In this example, we used giClust to analyze a number of histone modification datasets.
Two histone modification datasets [ 26, 27] were investigated here.
We used all ENCODE TFBS datasets (encodeHaib, encodeSydh, encodeUTA, and encodeUW), histone modification datasets (encodeHistoneBroad, encodeHistoneUW, encodeHistoneUTA), and open chromatin datasets (encodeDukeDNase, encodeUWDNase, and encodeUNCFaire).
Currently, InCroMAP supports mRNA, microRNA, DNA methylation and protein modification datasets.
InCroMAP supports DNA methylation, messenger RNA, microRNA and protein modification datasets.
For example, to create benchmark datasets in this study, we binarized the modification signal level at each position using BinarizeBed in ChromHMM [ 15], which classified the signal at each position into 0 or 1 according to a Poisson background model.
Advances in methodological approaches and high-throughput analyses in the last two decades fostered the rapid accumulation of centromere-related datasets in different model organisms, giving access to information about DNA, RNA, proteins, and their epigenetic modifications.
The use of big datasets in education is not new.
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