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For instance, Xu et al. (2001) suggested gene expression data clustering based on MST, which rigorously converts a multidimensional clustering problem to a tree partitioning problem.
Our previous study suggested gene expression similarity across studies is more pronounced on the level of pathways and gene functional categories, rather than specific genes or transcripts [ 13].
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This suggests gene expression changes due to miR-499 that favor hypertrophy.
As our previous logistic regression models would suggest, gene expression level as measured by mRNA abundance was a poor predictor of gene functionality.
These preliminary data also suggest gene expression may be useful for studying IA and HI symptoms that relate to ADHD in TS and perhaps non-TS participants.
This observation is obviously in conflict with the conventional results that suggest gene expression always correlates inversely with nucleosome occupancy [ 1, 3, 28, 32].
In young adults, the log-fold change is 0 and values close to 0 therefore suggest gene expression as seen in young adults.
Our results are consistent with previous reports suggesting gene expression profiles of PSC-derived neurons cluster more closely with fetal rather than adult neurons (27).
Gene expression profiling work has even suggested host gene expression differences between resistant and susceptible interactions in the first 12 hours [ 62].
The molecular genetic basis of human brain lateralization is unknown, and recent studies have suggested that gene expression in the cerebral cortex is bilaterally symmetrical.
In parallel, we conducted a calorimetry study to confirm in vivo the metabolic orientations suggested by gene expression results.
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