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On the contrary, the gene regulatory network derived from the application of the MOO procedure includes several gene interactions known to be important in acid adaptation.
Pathway and gene network analyses of the genes in the signature revealed several gene interactions suggestive of apoptosis as a process possibly involved in the manifestation of necrosis of the liver from exposure to the hepatotoxicants.
The reconstructed Bayesian network from the toxic exposures of the hepatotoxicants revealed several gene interactions that are consistent with interactions in the pathway that was generated from curated scientific literature and points to apoptosis-related genes in necrosis-mediated toxicity.
Finally, pathway and gene network analyses revealed several gene interactions suggesting that apoptosis may be a consequence of the chain of events stemming from drug-induced liver injury and it leads to, or is concomitant with, the manifestation of necrosis of the liver from exposure of the hepatotoxicants in rats.
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From this research, several gene interaction networks inferred could provide clues for the mechanism of prostate cancer progression.
Using functional representations, we predict several gene interaction properties, such as protein protein interactions and cell-type specificity, more accurately than competing methods based on global correlations.
Moreover, based on the gene pairs identified by the SIG method, we can not only deeply interpret some previously unknown interactions between a pair of genes, but also infer several gene interaction networks involved in the mechanisms of prostate cancer progression.
Additional literature mining revealed several gene-gene interactions acting on cardiometabolic traits.
Finally, applying our approach to Saccharomyces cerevisiae suggested several new gene interactions with high confidence awaiting experimental validation.
Although several potential gene interaction networks focused on established nuclear receptor systems (e.g., Supplemental Figs. S1 and S2), enrichment analysis revealed that experimental targets mapped to process networks related to blood vessel morphogenesis (P=0.002) and regulation of angiogenesis (P=0.027).
Combined with a series of in silico analysis utilizing publicly available microRNA knowledge bases and published literature data, we have uncovered several microRNA-gene interactions that specifically target both the blood and lungs.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com