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Because gene expression profiles have not been reported for M-MuLV induced lymphomas, we compared the general pattern of gene expression in tumors compared to normal thymic tissue.
Because gene expression profiles of LSC may differ depending on the stage of the disease, we investigated the LSC population of each leukemic mouse separately and selected for analysis only those mice exhibiting advanced MPD but no blast crisis progression.
This supports the hypothesis that photoperiod is a major environmental cue for vertebrate reproduction [4] because gene expression profiles in the neuroendocrine brain were photoperiodically-regulated to some degree.
25– 28 Gene expression might provide novel insights into speciation because gene expression profiles have the ability to uncover phenotypes, which would not readily be visible via traditional approaches.
Previously published work from our group [ 13] has demonstrated that such subjects are appropriate controls for gene expression studies in children with polyarticular JRA because gene expression profiles of peripheral blood buffy coats of children with polyarticular JRA revert toward patterns indistinguishable from such healthy controls after treatment.
However, it is unclear whether such gene expression profile is specific characteristics of the cartilage tissue regenerated by the DN gel implantation or common characteristics of cartilage tissues regenerated with tissue-engineering techniques, because gene expression profiles of the tissue-engineered cartilage tissues have not been clarified as of yet.
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Because gene expression profiling showed that these patients had lower expression levels of MUM-1, it has been suggested that some mechanisms other than NF-kB pathway activation might be involved in Bcl-2 overexpression.
3 Because gene expression profiling is not routinely performed in the clinical setting, immunohistochemical surrogates using the estrogen receptor (ER), progesterone receptor (PR), and HER2 are used to classify breast cancers into subtypes, although this classification is not optimal.
Common logarithms of EST counts were binned into five bins (0 0.5, 0.5 1.0, 1.5 2.0, 1.5–2.0, and more than 2.0), because the gene expression profiles based on ESTs are very sparse sequences of discrete values of EST counts and the number of genes.
That is possibly because the gene expression profiles under comparison were generated under different conditions, such as different tissue samples, cell lines/types, treatment doses and time durations, disease/development stages, ages, genotypes/variations, and experiment protocols etc.
Because the gene expression profiles are very similar between UCs from the upper and lower tracts, it is unlikely that direct cytogenetic profile comparisons will find any significant differences.
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