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This relatively new method can be used to determine absolute gene expression levels and is far more accurate than DNA-microarraying, which commonly generates ratio-based data.
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While heat map views are commonly used to view ratio-based expression data as a graphical matrix, there is good evidence that for small differences color intensity is difficult to visually resolve.
Ratio based data normalization and selection of features were performed using Acuity 4.0 (Molecular Devices).
In microarray gene expression analysis, ratio based data normalization and selection of features were performed using Acuity 4.0 (Molecular Devices).
The arrays were hybridized with each time point and the time point 0 min for each strain, thus, mRNA level data for 15, 30 and 60 min reflects the induction respect time 0. Data were ratio-based normalized and a FDR of 5% was used to identify statistically significant data.
For ratio-based meta-analysis, two-channel data were reformatted as log2-ratios (infected/mock-infected), and one-channel data were converted to a two-channel-like format where mock-infection intensities were averaged prior to ratio.
Data were ratio-based normalized and processed using Acuity 4.0 (Axon Instruments).
This dye bias was compensated through a ratio-based, global normalisation of the data.
When using a ratio-based model to analyze the data, many degrees of freedom are used to estimate the array effect, explaining only a small proportion of the variability.
The nature and extent of number-rounding, and the distribution of data across each order in recall data indicated a logarithmic (ratio-based) mental process for assigning values.
This experimental design was chosen in order to conduct intensity-based analyses of data instead of ratio-based analyses.
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