生物学中的时标关联：早期动力学测量能否预测长期结果？
Connecting Timescales in Biology: Can Early Dynamical Measurements Predict Long-Term Outcomes?
机构信息
Department of Systems Biology, Blavatnik Institute at Harvard Medical School, Boston, MA 02115, USA; Laboratory of Systems Pharmacology, Blavatnik Institute at Harvard Medical School, Boston, MA 02115, USA; Broad institute of Harvard and MIT, Cambridge, MA 02142, USA.
Department of Pathology, Brigham and Women's Hospital, Boston, MA 02115, USA.
出版信息
Trends Cancer. 2021 Apr;7(4):301-308. doi: 10.1016/j.trecan.2020.12.008. Epub 2021 Jan 13.
Prediction of long-term outcomes from short-term measurements remains a fundamental challenge. Quantitative assessment of signaling dynamics, and the resulting transcriptomic and proteomic responses, has yielded fundamental insights into cellular outcomes. However, the utility of these measurements is limited by their short timescale (hours to days), while the consequences of these events frequently unfold over longer timescales. Here, we discuss the predictive power of static and dynamic measurements, drawing examples from fields that have harnessed the predictive capabilities of such measurements. We then explore potential approaches to close this timescale gap using complementary measurements and computational approaches, focusing on the example of dynamic measurements of signaling factors and their impacts on cellular outcomes.
从短期测量结果预测长期结果仍然是一个基本挑战。对信号转导动力学的定量评估，以及由此产生的转录组学和蛋白质组学反应，为细胞结果提供了基本的见解。然而，这些测量的实用性受到其时间尺度（数小时到数天）的限制，而这些事件的后果通常需要更长的时间才能显现。在这里，我们讨论了静态和动态测量的预测能力，从利用这些测量的预测能力的各个领域中举例说明。然后，我们探讨了使用互补测量和计算方法来缩小这一时间尺度差距的潜在方法，重点是信号转导因子的动态测量及其对细胞结果的影响的例子。
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