Suggestions(5)
Exact(7)
Independent analysis of patient microarray data resulted in the identification of 85 probe sets whose abundance changed significantly during the course of VAP (Table 2).
Unsupervised hierarchical clustering of the microarray data resulted in the expected separation between the OSE and Cepi samples.
Hierarchical clustering of the microarray data resulted in clear separations between the OSE, Cepi, NS, and CS samples.
The analysis of the microarray data resulted in 3.309 (actinomycin D), 1.019 (doxorubicin) and 134 (vincristine) probesets that showed significant expression changes.
Statistical analysis of our microarray data resulted in a list of differential genes that were common between all E. arvense samples.
Analysis of the microarray data resulted in 160 candidate genes differentially regulated in the highest dose (8 mg/kg BW PCB 153) group, using SAM (Significance Analysis of Microarrays) at FDR (False Discovery Rate) 10% (Additional file 1 Table S1 Table
Similar(53)
Therefore we examined the microarray data resulting from the Sakai strain, using genes within the K12 genome.
First, for each TF we infer its activity in each time point of the microarray data, resulting in an activity profile for it.
We integrate the microarray cell cycle gene expression data with the ChIP-chip data to infer TF activities at 18 time points of the microarray data, resulting in 203 activity change score (AC score) profiles each corresponding to a TF.
Subsequently, the reference ASp value distribution analysis was repeated using the mAS values; i.e., the universal set of pathway associations integrated exclusively of the links supported by microarray data, resulting in 1,350 potential associations among pathways.
Therefore, to flesh out this hypothesis, the Ingenuity Pathway Analysis software tool [ 21, 26] was used to analyze the microarray data resulting in the identification of nine networks that responded to SMF exposure in hEDB LVED cells (Table 5; data analysis is shown for cells subject to five days of continuous SMF exposure and the annotated networks are provided in Additional file 1).
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com