Using systems biology to define the essential biological networks responsible for adaptation to endurance exercise training
Using systems biology to define the essential biological networks responsible for adaptation to endurance exercise training
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DOI：
10.1042/bst0351306
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发表时间：
2007-11-01
影响因子：
3.9
通讯作者：
Timmons, J. A.
中科院分区：
文献类型：
--
作者：
Keller, P.;Vollaard, N.;Timmons, J. A.
我们预测，在考虑生理适应时，RNA水平的调节与蛋白质水平的调节一样多样和强大。非编码RNA分子，如miRNAs (microRNAs)，已经成为mRNA转录后调控的强大机制。为了确定miRNA在人类骨骼肌生物学中的作用，我们开始对耐力运动训练前后的肌肉RNA进行分析。利用原始数据的无偏分析策略建立了健壮的肌肉分子表型，反映了基因本体和网络分析的统计能力。因此，我们可以确定骨骼肌转录组的结构特征，识别通过训练激活的离散网络，并利用生物信息学预测来建立非编码RNA调制和Affymetrix表达谱之间的相互作用。
We predict that RNA level regulation is as diverse and powerful as protein level regulation when considering physiological adaptation. Non-coding RNA molecules, such as miRNAs (microRNAs), have emerged as a powerful mechanism for post-transcriptional regulation of mRNA. In an effort to define the role of miRNA in human skeletal-muscle biology, we have initiated profiling of muscle RNA before and after endurance exercise training. The robust molecular phenotype of muscle is established using unbiased analysis strategies of the raw data, reflecting the statistical power of gene ontology and network analysis. we can thus determine the structural features of the skeletal-muscle transcriptome, identify discrete networks activated by training and utilize bioinformatics predictions to establish the interaction between non-coding RNA modulation and Affymetrix expression profiles.