Transcriptomics is the study of entire RNA populations in a cell or organism, revealing genetic information through mRNA analysis.
转录组学是研究细胞或生物体中所有RNA分子群落的学科,通过mRNA分析揭示遗传信息。
By comparing transcriptomes across different developmental stages, researchers can track gene expression changes.
通过比较不同发育阶段的转录组,研究人员可以追踪基因表达的变化。
Single-cell
transcriptomics allows for the analysis of gene expression at the cellular level, providing insights into cellular diversity.
单细胞转录组学允许在细胞水平上分析基因表达,提供细胞多样性的见解。
Transcriptomics has been instrumental in identifying disease biomarkers and understanding disease mechanisms.
转录组学在发现疾病标志物和理解疾病机制方面发挥了关键作用。
Meta
transcriptomics investigates the transcripts in environmental samples, revealing the微生物 community's activity.
宏转录组学研究环境样本中的转录本,揭示微生物群落的活动情况。
Transcriptomic profiling helps predict drug response in cancer patients, guiding personalized treatment plans.
转录组表型分析有助于预测癌症患者对药物的反应,指导个性化治疗策略。
The analysis of
transcriptomics data from plants under stress conditions can help in developing stress-resistant crops.
在分析植物在压力条件下的转录组数据,有助于培育抗逆性作物。
Transcriptomics can be used to study the impact of genetic engineering on an organism's gene expression.
转录组学可用于研究基因工程对生物体基因表达的影响。
In evolutionary studies,
transcriptomics can reveal the genetic changes that occur over time.
在进化研究中,转录组学可揭示随时间发生的基因变化。
Transcriptomics is often combined with other -omics technologies (e.g., proteomics, genomics) for a comprehensive understanding of biological systems.
转录组学常与其他-组学技术(如蛋白质组学、基因组学)结合,以全面了解生物学系统。
Modern technologies such as big data and AI offer diversified research methods to further explore TCM, while the application of metabolomics, genomics and transcriptomics made it possible to know TCM from a micro-level perspective.
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