SGER: Biologically Inspired Computation to Understand Regulatory Gene Networks

我们寻求启动一项探索性研究计划，旨在创建设计工具，用于设计、优化、模拟和测试由生物学基本机制构建的生物电路；具体来说，是由 DNA、RNA 和蛋白质相互作用组成的机制。这些电路是分散的、异步的，但很容易复制，因为它们的基本组件是由自然界中已经存在的元素创建的，并且可以使用相同的原理进行合成、控制和降解。它们利用的基本生物学原理是：聚合酶诱导的复制、转录激活控制的转录、翻译成蛋白质、小RNA的干扰以及通过染色体外质粒的调节。由于基本的设计原理，以这种方式创建的生物电路可以很容易地转染到简单的原核生物（例如大肠杆菌）、真核生物（例如酵母）以及细胞系中。我们希望通过研究设计的生物回路（其操作是已知的、建模的和已经研究过的）与宿主生物体基因的未知功能之间的相互作用，更好地理解感兴趣的生物机制。通过这种方式，所提出的研究计划扩展了当前基于敲入突变体、敲除突变体、染色体外质粒扰动的基因和通过RNAi干扰的功能基因组学方法。因此，最终所提出的研究旨在通过使用正向工程和逆向工程范式的计算和数学方法来理解基因网络。对于正向工程，我们直接解决与遗传电路有关的各种主题 - 特别是，我们专注于利用调控基因、RNA 和蛋白质创建新型人工电路。对于逆向工程，在我们其他相关研究的背景下，我们还解决了通过分析大量数据（例如转录组数据）中的时间过程数据的技术来推断基因网络的问题，但不排除蛋白质组或代谢组数据。此外，很明显，在不久的将来，这些方法可以在基因治疗、生物体基因改造甚至大规模系统中发挥重要作用，以解决具有挑战性的计算问题。主要的计算挑战是使用简单的构建块（例如组合逻辑门（AND、NOT、XOR等）、仲裁器电路（Muller C电路）和存储器元件（FIFO队列元件））开发延迟独立异步电路的新颖设计原理。

We seek to initiate an exploratory research program aimed at creating design tools for designing, optimizing, simulating and testing biological circuits built out of basic machineries of biology; specifically, mechanisms composed of DNA, RNA and protein interactions. These circuits are dispersed, asynchronous but are easily replicable as their basic components are created out of those elements that already occur in nature and can be synthesized, controlled and degraded using the same principles. The basic biological principles that they utilize are: polymerase-induced replication, transcription controlled by transcription activation, translation into proteins, interference by small RNA, and modulation via extra-chromosomal plasmids. Because of the underlying design principles, biological circuits created in this manner can be easily transfected into simple prokaryotic organism such as E. coli, eukaryotic organisms such as yeast as well as cell lines. We hope to gain a better understanding of the biological mechanisms of interest by studying the interaction between the designed biological circuit, whose operation is known, modeled and already studied, and the unknown function of the genes of the host organism. In this manner, the proposed research program extends the current functional genomics methods based on knock-in mutants, knock-out mutants, genes perturbed by extra-chromosomal plasmids and interference through RNAi.Thus ultimately the proposed research is aimed at understanding gene networks through computational and mathematical methods using both forward engineering and reverse engineering paradigms. For forward engineering, we directly address various topics dealing with genetic circuits - in particular, we focus on creating novel artificial circuits out of regulatory genes, RNAs, and proteins. For the reverse engineering, in the context of our other related research, we have also addressed the problem of inferring gene networks with techniques analyzing time-course data in abundance data, such as transcriptome data, but not excluding proteome, or metabolome data. Furthermore, it should be apparent that in the near future these methods could play an important role in gene therapy, genetic modification of organisms or even large-scale systems to solve challenging computational problems.The major computational challenge is the development of novel design principles for delay-independent asynchronous circuits using simple building blocks such as combinatorial logic-gates (AND, NOT, XOR, etc.), arbiter circuits (Muller C-circuit) and memory elements (FIFO queue elements).