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Hierarchical clustering and principal component analyses of gene expression across microarray samples revealed that most of the variation in gene expression was associated with developmental staging.
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Microarray analysis of liver samples revealed 134 differentially expressed transcripts (adjusted P < 0.05; fold changes > 1.5).
Microarray profiling of liver samples revealed expression patterns characteristic of vitellogenic females of which only ~64% were found to be putatively regulated by E2.
Tissue microarray analysis of tumour samples revealed that high RUNX2 expression correlates with the triple-negative breast cancer subtype and with lower patient survival rates compared with samples displaying low RUNX2 expression.
However, to date there is no evidence that the clinical use of HDAC inhibitors is associated with such reactivation., Moreover, in patients treated with panobinostat for cutaneous T-cell lymphoma (CTCL), microarray analysis of tumor samples revealed that approximately 5% of genes displayed altered expression with the majority being repressed.
Custom-designed, high-resolution microarray analysis of additional ACD/MPV samples revealed one microdeletion harboring FOXF1 and two distinct microdeletions upstream of FOXF1, implicating a position effect.
Microarray analysis from human brain samples revealed a significant decrease of about 45% in the expression of CACNA1G, that encodes the low-voltage-activated Cav3.1 T-type Ca2+ channel, in aged non-diseased (74 95) compared with young non-diseased (20 59) individuals.
Genome-wide microarray approach using complex human tissue samples revealed novel expression patterns, reflecting some important features of mesothelioma biology that should be further explored.
Furthermore, tissue microarray using 55 ovarian cancer patient samples revealed that patients with a lower level of ABCA1 expression are associated with shorter progress-free survival (P = 0.038).
A meta-analysis of around 800 data sets from a consortiumwide microarray study of two standardized biological samples revealed poor correlation across laboratories and between platforms.
A meta-analysis of five microarray gene expression studies of 60 samples revealed seven genes: BCL2, COL1A2, COL3A1, COL5A2, CXCL12, TIMP4, TNC that are very likely to be involved in the genesis of IAs [ 57].
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