申请人提出了“匀质功能关联网络”的概念，以及基于这类网络分析组学变化的整体生物学意义的方法：“基因集功能关联分析（GSLA）”。在与实验结合的研究中，发现GSLA具有独特的，能够依据“现在观察到的组学变化”解析“将要发生的整体功能改变”的能力。GSLA发现了一些其它方法无法发现的生物学规律，例如，低出生体重增加成年慢性疾病风险的长期分子机制，干细胞治疗暴发性肝衰竭的生物途径机制。这些发现都得到了实验验证。但是，当前的GSLA仍有一定局限：一，仅能通过组学变化预期哪些生物途径或生理过程将受到影响，但不能判断影响的方向（激活／抑制）；二，缺乏具有广泛代表性的测试案例集，来系统比较GSLA和其它方法的解析组学变化整体生物学意义的能力。本项目将从这两个方面进一步发展GSLA，建立经过严格检验的实用工具，并在具体的分析应用中（优化体外诱导干细胞定向分化为肝实质细胞的方法），检验和改进其分析能力。

Previously, we have established the concept of "homogenous functional interaction network", and developed a method to use this type of network for interpretation of the overall high-level functional impact of an observed omics change. This method is called gene set linkage analysis, or GSLA. .When used in real world data analyses, this method exhibited a unique capability to anticipate the "future" functional consequences of a "currently" observed omics change. This unique capability has already enabled GSLA to make several discoveries that could not be made with other approaches. For instances, the molecular mechanisms linking low birth-weight infants to their known health risks in adulthood, and the biological process that plays a critical role in the therapeutics of human bone marrow mesenchymal stem cells rescuing fulminant hepatic failure. These discoveries have all been validated with experiments. However, the current GSLA method is still limited, in the way that 1) it only gives the biological or physiological processes, the functions of which are likely affected by the omics change, but GSLA does not compute the expected directions of these functional impacts; 2) we still do not have a comprehensive and representative dataset of test cases, which can be used to rigorously evaluate the capability of GSLA in interpretation of observed omics changes, and compare the capability of GSLA with those of the other approaches. This application aims to improve the current GSLA method in these two directions. We will build a new GSLA tool that is rigorously tested with a well organized dataset of test cases, and will evaluate the analysis capability of GSLA in a case study: optimization of the protocol for in-vitro directed differentiation of stem cells to hepatocytes.