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These calculations are performed for all samples and pathways.
In the last case we bootstrapped samples and pathways over 100 and 1000 iterations.
We first integrated gene expression profiles and biological pathway information to explore the underlying associations between genes differently expressed among normal and BC samples and pathways enriched from these genes.
To identify homogeneous subtypes, a two way clustering of the aberration profiles across samples and pathways was done using hierarchical clustering with the same distance metric and linkage method.
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For this work, we performed a systematic analysis of the major routes involved in crosstalk phenomena with the estrogen pathway – based on gene expression experiments (819 samples) and pathway analysis (493 samples) – for biopsy-captured tissue and contrasted in two independent datasets with in vivo and in vitro pharmacological stimulation.
For pathway-based clustering of samples, we constructed a matrix composed of optimal principal component scores for each sample and pathway.
In contrast to the low level of recurrence in these melanoma samples at the individual gene level, we found that six pathways were shared by five of the samples, and four pathways (G protein, WNT, cadherin signaling and melanogenesis) were common to six (see Table 3).
Columns represent individual samples, and rows pathways.
One could compare, for example, drug treated samples to untreated samples and predict pathways targeted by the compound.
By adopting a whole genome profiling approach this study has identified gene signatures differentiating SpA from non-SpA samples and highlighting pathways that might play key pathophysiological roles in AS.
Higher correlation with the drug signature corresponded to a higher rate of survival, though paradoxically, this higher correlation is also closer to the average expected correlation between the patient samples and the pathway signature.
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