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qPCR analysis of Hox-A cluster gene expression in various ES cell lines expressing the NupFG-HoxA9 fusion, Nup98FG, or HoxA9.
In the exploration of transcriptional regulatory networks, an important task is to cluster gene expression data to identify groups of genes with similar patterns and hence similar function.
Utilizing graph-theoretic and statistical techniques, CLICK is generally used to cluster gene expression profiles.
Consistent with these results, FLT3, HLF and JAG2 expression correlated with HOX A cluster gene expression in human leukemia samples.
Menin-dependent histone modifications via MLL in the Hoxa9 locus may further recruit/stabilize Cdx4 in the chromatin and thus, establish an optimal level of Hoxa cluster gene expression at certain developmental stage of hematopoietic cells, such as AT1 cells.
A number of algorithms were proposed to cluster gene expression profiles.
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The kinetics of patulin cluster genes expression was studied under patulin-permissive conditions (natural apple-based medium) and patulin-restrictive conditions (Eagle's minimal essential medium), and demonstrated a significant association between gene expression and patulin production.
In this section, we continue to use the estimated coefficient functions as features to cluster genes expression data to study the genome-wide transcriptome.
A new algorithm is presented for fitting the plaid model, a biclustering method developed for clustering gene expression data.
In this manuscript we describe a methodology for clustering gene expression correlation profiles in the C57Bl/6J mouse cortex to identify large-scale genetic relationships between layers and areas.
It is also intended to introduce one of the main problems in bioinformatics – clustering gene expression data – to the operations research community.
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