ABI Innovation: Bridging the Gap between the Transcriptome and the Proteome to Study Inter-cellular Signaling

系统生物学促进了对生理过程的沿着多条探究线同时进行的研究。 然而，捕获某些类型的数据的技术（例如，基因表达水平）比获得其它类型数据的方法（例如，蛋白质水平）。为了消除这一差距，这项研究将开发一种原则性很强的方法，根据从转录实验中收集的数据，优先考虑昂贵而耗时的蛋白质组学实验。该团队将使用新颖而复杂的算法来计算有向Steiner非循环图来驱动这些分析。他们将使用他们的方法来研究生物学中的一个基本问题：不同类型的细胞如何在组织和器官中发现的复杂环境中相互交流？ 他们将使用一种新的体外三维肝脏模拟物来解决这个问题，该肝脏模拟物包含两种不同的肝细胞类型。 该项目的教育部分将通过一个夏季研究所为四名本科生举办“工程组织中的计算驱动实验生物学”，将计算思维注入本科生的生物学和工程学，包括与项目相关的主题讲座和一个单一的合作研究项目。让所有学生参与一个单一的研究项目将使他们接触到团队科学，并让他们了解计算机科学，组织工程和实验细胞生物学如何无缝交织在一起来研究细胞过程。通过开发研究细胞间信号传导的创新解决方案，该项目将为细胞间和器官水平系统生物学的进步铺平道路。 该项目将通过将新的蛋白质组学数据与现有测量相结合来开发一个组合的计算-实验管道，以改进我们的模型和算法。方法，算法和软件将是一个有价值的补充，新兴的一套工具，使用计算分析，以优先考虑新的实验。该项目的研究、软件和数据将在http://bioinformatics.cs.vt.edu/~murali上提供。

Systems biology promotes studying physiological processes along multiple lines of inquiry simultaneously. However, technologies to capture some types of data (e.g., gene expression levels) are more advanced, more comprehensive, and less expensive than methods to obtain other types of data (e.g., protein levels). To remove this gap, this research will develop a well-principled approach to prioritize expensive and time-consuming proteomic experiments based on data collected from transcriptional experiments. The team will drive these analyses using novel and sophisticated algorithms to compute directed Steiner acyclic graphs. They will use their methodology to study a fundamental question in biology: how do different cell types communicate with each other in the complex environment found in tissues and organs? They will address this question using a novel in vitro three-dimensional liver mimic that contains two different hepatic cell types in a layered configuration. The educational component of this project will infuse computational thinking into biology and engineering at the undergraduate level via a summer research institute on "Computationally-Driven Experimental Biology in Engineered Tissues" to four undergraduate students, consisting of lectures on project-related topics and a single collaborative research project. Involving all the students in a single research project will expose them to team science and give them an appreciation of how computer science, tissue engineering, and experimental cell biology can be seamlessly interwoven to study cellular processes. By developing innovative solutions to study inter-cellular signaling, this project will pave the way for advances in inter-cellular and organ-level systems biology. This project will develop a combined computational-experimental pipeline by integrating new proteomic data with existing measurements in order to refine our models and algorithms. The methodology, algorithms, and software will be a valuable addition to the emerging set of tools that use computational analysis to prioritize new experiments. The research, software, and data resulting from this project will be made available at http://bioinformatics.cs.vt.edu/~murali.