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Two predictive signatures for breast cancer identified by microarray analysis have been further developed into clinical multi-gene panel tests [5].
Genetic markers for thyroid cancers identified by microarray analysis have offered limited predictive accuracy so far because of the few classes of thyroid lesions usually taken into account.
Global expression studies by microarray analysis have identified significant changes in the expression of several hundreds of genes in ICF, involved in immune function, development and neurogenesis as well as lymphogenesis, signal transduction and apoptosis [14], [21].
Differences in gene expression, as determined by microarray analysis, have been reported for fetal versus aged skin [ 14].
All the results obtained by microarray analysis have been deposited in the NCBI Gene Expression Omnibus GEOO) database as accession number GSE6534.
As elaborated above, our results derived by microarray analysis have revealed significant changes in a large number of genes representing proteins that participate in multiple pathways, including various immunological and biochemical pathways (Table 1).
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Gene expression profiling by microarray analysis has offered a new way to classify human breast tumours.
Gene expression profiling by microarray analysis has identified breast cancer signatures that are important for prognosis and treatment.
Underestimation of fold changes by microarray analysis has been reported previously, reflecting the higher sensitivity of qRT-PCR [ 5, 13].
Inhibition of the nonsense-mediated mRNA decay pathway followed by microarray analysis has been successfully applied to cancer cell lines to identify protein truncating mutations that may underlie sporadic forms of cancer [ 19, 23, 25- 29, 54].
Forty-six of the 67 genes with undetectable levels of expression in the leaf sample in the microarray analysis had 0 MPSS tags in the leaf MPSS library (LEF), while 75 of the 95 genes detected by microarray analysis had more than one tag in the MPSS leaf library.
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