Sentence examples for analysis in experiments from inspiring English sources

We investigate the application of numerical bifurcation analysis for studying the solution set of such noise contaminated zero problems, which is highly relevant in the context of equation-free analysis (coarse grained analysis) and bifurcation analysis in experiments, and develop specialized algorithms to address challenges that arise due to the presence of noise.

All experiments were tested with an ANOVA (or t-test for contrast analysis in experiments 1 and 2) using the statistical package JMP [31].

It is also worthy of note that MMP1 is also up regulated in endothelial cells according to SAGE library analysis in experiments 2 and 3.

In addition, its hierarchal structure allows a more specific disease term to be binned to a more general disease term at different levels which is especially useful for Disease Ontology enrichment analysis analogous to gene ontology enrichment analysis in experiments applying high throughput technologies.

Because it was difficult to estimate (m_p) with our experimental setup, for the analysis in Experiment 3, we used a representative value taken from the literature [31]: (m_p = 0.1 times 10^{-3}) kg.

We used mean responses per subject as sample points in the statistical analysis in Experiment 1, but to avoid pseudoreplication we designed Experiments 2 and 3 with sufficient numbers of exemplars of local and foreign songs to use mean responses per exemplar as sample points.

Apart from the correlation analysis in Experiment #1 in which we set alpha to 2.5% due to multiple comparison between Q1, Q3, and Q4, we set alpha to 5% in all remaining tests.

The experimental procedure was identical for experiment 1 and 2. The only difference was that we collected blood samples for BNDF analysis in experiment 1 and saliva samples for cortisol analysis in experiment 2. The participants completed several questionnaires.

Similarly, WRKY28 was not found to be robustly co-expressed with SID2 in this study and was not included in the 518 genes selected for analysis in experiment #2.

A priori, cofactor analysis was expected to have higher power than individual chromosome analysis especially in experiments with lower power to detect QTL.

A typical one-way analysis setup in experiments looking for potential biomarkers for disease is the diseased healthy differential analysis.