Biocharts: Unifying Biological Hypotheses with Models and Experiments

H. Kugler
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引用次数: 2

Abstract

Understanding how biological systems develop and function remains one of the main open scientific challenges of our times. An improved quantitative understanding of biological systems, assisted by computational models is also important for future bioengineering and biomedical applications. We present a computational approach aimed towards unifying hypotheses with models and experiments, allowing to formally represent what a biological system does (specification) how it does it (mechanism) and systematically compare to data characterizing system behavior(experiments). We describe our Biocharts framework geared towards supporting this approach and illustrate its application in several biological domains including bacterial colony growth, developmental biology, and stem cell population dynamics.
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生物图:用模型和实验统一生物学假说
了解生物系统的发展和功能仍然是我们这个时代的主要科学挑战之一。在计算模型的辅助下,对生物系统的定量理解的改进对未来的生物工程和生物医学应用也很重要。我们提出了一种计算方法,旨在将假设与模型和实验统一起来,允许正式表示生物系统做什么(规范),它是如何做的(机制),并系统地与表征系统行为的数据进行比较(实验)。我们描述了我们的生物图表框架,旨在支持这种方法,并说明其在几个生物学领域的应用,包括细菌菌落生长,发育生物学和干细胞群体动力学。
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