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Commercial microarray platforms perform better than the home-spotted mainly due to their higher reproducibility.
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By evaluating the performance of the genomic model in two independent validation cohorts with different microarray platforms performed at different medical centers, we demonstrate the potential applicability of our findings for real-world use.
Miao et al. (10) initiated Tetrahymena functional genomics by establishing the first T. thermophila microarray platform performing a genome-wide investigation of gene expression during the three major physiological and developmental stages of the T. thermophila life cycle.
Hybridization of total RNAs derived from SYT-SSX2 and pOZ vector-infectant transcripts to Affymetrix microarray platforms was performed and transcript changes were expressed as Log2 ratios of SYT-SSX2 signal intensity to pOZ control [where the Log2 ratio (x) represents 2x fold increases (or decreases) in transcript level].
To combine these datasets obtained from different microarray platforms, we performed the following pre-processing methods.
First, pre-processing and the selection of representative sequences of the AQPs from the four different microarray platforms were performed using Bioconductor and R as previously described [ 26].
For each of the four microarray platforms, we performed a statistical power analysis of adjacent targets surrounding a specific locus on a chromosome.
We have compared the effective gene coverage in the mouse genome of different commercial and noncommercial oligonucleotide microarray platforms by performing an in-house gene annotation of probes.
All downstream analyses, including differential gene expression, IPA analysis based on sense and antisense strand data, and technical comparisons between RNA-seq and microarray platforms were performed using data from the remaining six animals (i.e. 12 RNA-seq libraries).
Gene expression profiling the 44 K microarray platform was performed in root samples at 1, 5, and 10 days after –P and ++P stress treatments.
We were able to map all 16 genes to our microarray platform and performed hierarchical cluster analysis based on the expression of these 16 genes for the series of 71 tumors (Additional file 5 part a).
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