Organisms have evolved a broad array of complex signaling mechanisms that allow them to survive in a wide range of environmental conditions. They are able to sense external inputs and produce an output response by computing the information. Synthetic biology attempts to rationally engineer biological systems in order to perform desired functions. Our increasing understanding of biological systems guides this rational design, while the huge background in electronics for building circuits defines the methodology. In this context, biocomputation is the branch of synthetic biology aimed at implementing artificial computational devices using engineered biological motifs as building blocks. Biocomputational devices are defined as biological systems that are able to integrate inputs and return outputs following pre-determined rules. Over the last decade the number of available synthetic engineered devices has increased exponentially; simple and complex circuits have been built in bacteria, yeast and mammalian cells. These devices can manage and store information, take decisions based on past and present inputs, and even convert a transient signal into a sustained response. The field is experiencing a fast growth and every day it is easier to implement more complex biological functions. This is mainly due to advances in in vitro DNA synthesis, new genome editing tools, novel molecular cloning techniques, continuously growing part libraries as well as other technological advances. This allows that digital computation can now be engineered and implemented in biological systems. Simple logic gates can be implemented and connected to perform novel desired functions or to better understand and redesign biological processes. Synthetic biological digital circuits could lead to new therapeutic approaches, as well as new and efficient ways to produce complex molecules such as antibiotics, bioplastics or biofuels. Biological computation not only provides possible biomedical and biotechnological applications, but also affords a greater understanding of biological systems.

中文翻译：

---

合成生物学：深入了解生物学计算。

生物进化出了各种各样的复杂信号传导机制，使它们能够在各种环境条件下生存。他们能够通过计算信息来感知外部输入并产生输出响应。合成生物学试图合理地设计生物系统以执行所需的功能。我们对生物系统的越来越多的理解指导了这种合理的设计，而建筑电路电子学的巨大背景定义了该方法。在这种情况下，生物计算是合成生物学的一个分支，旨在利用工程化的生物图案作为构建模块来实现人工计算设备。生物计算设备被定义为能够按照预定规则整合输入和返回输出的生物系统。在过去的十年中，可用的合成工程设备数量呈指数增长。在细菌，酵母和哺乳动物细胞中已经建立了简单而复杂的电路。这些设备可以管理和存储信息，根据过去和现在的输入做出决定，甚至可以将瞬态信号转换为持续响应。该领域正在快速发展，并且每天都更容易实现更复杂的生物学功能。这主要是由于体外DNA合成技术的进步，新的基因组编辑工具，新颖的分子克隆技术，不断增长的零件库以及其他技术进步。这使得现在可以在生物系统中设计和实现数字计算。可以实现并连接简单的逻辑门，以执行新颖的所需功能或更好地理解和重新设计生物过程。合成生物数字电路可能会导致新的治疗方法，以及产生复杂分子（例如抗生素，生物塑料或生物燃料）的新型有效方法。生物计算不仅提供了可能的生物医学和生物技术应用，而且使人们对生物系统有了更深入的了解。