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Thus, for microarray analyses involving complex tissues such as brain, low fold changes in gene expression may indicate large fold changes in a subset of cells or cells in a particular region of the tissue and should not be overlooked.
This has been confirmed by recent studies using global microarray analyses involving methylated DNA immunoprecipitation (MeDIP) to assess the DNA methylation status of the Xi relative to the Xa in human primary cells (Weber et al. 2007).
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Analyses involving the microarray suite (MAS) 5.0 detection algorithm revealed 14,590 genes expressed in UNMs, 12,967 in BCP, 12,514 in TCP, 5939 in MPGs and 5945 in GPGs, in comparison with 16,000 in callus cells, 17,383 in roots and 17,424 in leaves (Additional file 2).
ZC participated in the design of the study, performed the qRT-PCR and microarray analyses, and involved in the interpretation of the data.
Notably, this result implies that the RNAs identified here as surveillance substrates would predominately be overlooked in microarray analyses that involve oligo dT) selection or priming for cDNA synthesis.
Our microarray analyses identified genes involved in adult thoracic dorsum formation.
Analyses involved logistic regression.
In addition to genes involved in reproduction, microarray analyses revealed differential expression of genes involved in insect immunity between Wolbachia-infected and uninfected D. melanogaster larval testes.
These include gene expression profiling in differentiating male and female embryonic gonads [27], microarray analyses to identify genes involved in ovary development [28] and time course profiling of testicular gene expression during spermatogenesis [29].
However, few of these studies involved microarray analyses, general expression patterns in cancer cell lines or clinical relativity at the same time.
Microarray analyses confirmed that those genes involved in cell cycle functions are highly upregulated in regenerator compared with degenerator.
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