Sentence examples for methodologies gene expression from inspiring English sources
In between there are a variety of protein detection methodologies, gene expression measurements, mRNA (transcriptome) profiling, and biochemical metabolite (pathway) assays.
Current methodologies for gene expression profiling in small RNA samples, especially those from single cells, are very limited.
Among these papers 152 (51.9%) concentrated on the presentation of new methodologies for gene expression data analysis, and 141 (48.1%) papers mainly contributed application studies, e.g. discoveries directly relevant to molecular biology and clinical studies.
Methodology included gene expression measures from microarrays, Gene Score Resampling for global ontological profiling, and semi-quantitative RT-PCR.
To integrate these two measures into a single analysis, here we transfer the volcano plot methodology from gene expression analysis to genetic association studies.
To further illustrate the potential prognostic application of pathway L values, we implemented classification models built on genes identified by a published methodology for gene expression analysis, and compared the resulting prediction performances against the results reported above.
Recently, applying the same methodology differential gene expression pattern in normal and OA cartilage tissue was identified [ 4].
We have applied this new fuzzy logic methodology on gene expression data information obtained from public available datasets and our own patients cohort.
We illustrate the application of the methodology with gene expression data obtained from various microarray experiments with different conditions and diseases.
This methodology considers gene expression values as a quantitative trait that can be mapped to chromosomal locations in a segregating population.
Some of these changes have not been previously detected by microarrays, likely due to microarray saturation of signal with high levels of expression and/or higher sensitivity of the RNA-Seq methodology to gene expression changes with relatively low overall fold-difference between the groups.
