首页|The molecular core of transcriptome responses to abiotic stress in plants: a machine learning-driven meta-analysis
The molecular core of transcriptome responses to abiotic stress in plants: a machine learning-driven meta-analysis
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NETL
NSTL
According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from biorxiv.org: “Understanding how plants adapt their physiology to overcome severe stress conditions is vital in light of the current climate crisis. “This remains a challenge given the complex nature of the underlying molecular mechanisms. To provide a full picture of stress mitigation mechanisms, an exhaustive analysis of publicly available stress-related transcriptomic data was conducted. We combined a meta-analysis with an unsupervised machine learning algorithm to identify a core of stress-related genes. To ensure robustness and biological significance of the output, often lacking in meta-analyses, a three-layered biovalidation was incorporated. “Our results present a stress gene core, a set of key genes involved in plant tolerance to a multitude of adverse environmental conditions rather than specific ones.
NETL
NSTL
