Pathway-Guide: A novel tool for the analysis of signaling and metabolic pathways

描述（由申请人提供）：一旦被誉为圣杯，获得疾病和正常之间不同的基因，蛋白质或代谢物的全面列表的能力今天是常规的。然而，到目前为止，高吞吐量的圣杯还没有交付。尽管这种高通量比较已经变得相对容易进行，但理解导致疾病的现象仍然具有挑战性。信号和代谢途径是描述生物体各个子系统中发生的基因信号和生化反应的复杂图。目前的方法，旨在帮助我们了解潜在的生物现象，通过使用测量的差异，以确定显着影响的途径是相当不成熟的。许多（如果不是所有的话）这样的方法都把这些通路当作简单的基因组，而忽略或没有充分利用这些通路的本质：描述基因相互作用的复杂方式的图表。我们建议开发一种软件产品，用于在高通量数据的背景下分析基因信号和代谢途径，如DNA微阵列。该方法的基本原理已通过实施可从PI的学术网站免费提供的工具进行了测试。这些工具现有11，266名注册用户，他们已经使用并信任我们的软件。这个用户群构成了Advaita的独特资产。我们设想的产品将具有许多独特的能力，包括：i）考虑特定基因之间的相互作用; ii）计算独特的“影响因子”，以表征生物体的给定子系统在给定条件下受到的影响; iii）找到疾病和药物的作用机制; iv）查明最佳治疗干预的潜在点;以及v）通过监测大量参数（基因表达水平、代谢物等）来检测活生物体中的质的变化。该产品有潜力：i）通过提供更少但更好的候选药物缩短药物开发周期，ii）帮助理解疾病和药物机制，iii）检测生物有机体的质变。这种分析方法的科学有效性已经在许多应用中的真实的数据上得到了验证（一些已发表，其他的在这里描述为初步结果）。在超过36，000次基准试验中证明了技术可行性。本产品的商业有效性已通过实现包括上述前2个功能的原型类型进行了验证。该原型已经出售给3个客户，尽管它只实现了最终功能集的一小部分，而且这些客户已经可以使用我们竞争对手提供的软件产品。 公共卫生相关性：拟议研究的好处预计将影响许多研究领域，从癌症到肥胖，到衰老以及任何其他生命科学领域，其中高通量方法（例如DNA微阵列，蛋白质微阵列，代谢组学等）被使用。可以从这项研究中受益的生物用户社区包括在任何生物领域和任何生物体中使用这种高通量方法的任何生命科学研究人员，从酵母到果蝇，到小鼠，到人类。

DESCRIPTION (provided by applicant): Once heralded as the Holy Grail, the capability of obtaining a comprehensive list of genes, proteins or metabolites that are different between disease and normal is routine today. And yet, the holy grail of high-throughput has not delivered so far. Even though such high-throughput comparisons have become relatively easy to perform, understanding the phenomena that cause the disease is as challenging as ever, if not more so. Signaling and metabolic pathways are complex graphs describing genes signaling and biochemical reactions that take place in various subsystems of the organism. The current methods that aim to help us understand the underlying biological phenomena by using the measured differences to identify significantly impacted pathways are rather unsophisticated. Many if not all such methods of- ten treat the pathways as simple sets of genes, and either ignore or under-utilize the very essence of such pathways: the graphs that describe the complex ways in which genes interact with each other. We are proposing the development of a software product for the analysis of gene signaling and metabolic pathways in the context of high throughput data, such as DNA microarrays. The fundamentals of the approach have been tested through the implementation of tools available for free from the PI's academic web site. These tools have an existing user base of 11,266 registered users who already use and trust our software. This user-base constitutes a unique asset for Advaita. The product we envisage will have a number of unique capabilities including the ability to: i) take into consideration the interactions between specific genes; ii) calculate a unique "impact factor" that characterizes how impacted a given subsystem of the organism is in the given condition; iii) find the mechanisms of action for diseases and drugs; iv) pinpoint potential points of optimal therapeutic intervention; and v) detect qualitative changes in a living organism by monitoring a large number of parameters (gene expression levels, metabolites, etc.). This product has the potential to: i) shorten the drug development cycle by providing fewer but better drug candidates, ii) help with the understanding of disease and drug mechanisms, iii) detect qualitative changes in biological organisms. The scientific validity of this analysis approach has been verified on real data in a number of applications (several published, others described here as preliminary results). The technical feasibility was demonstrated in over 36,000 benchmark trials. The commercial validity of this product has been verified by implementing a proto- type including the first 2 of the capabilities above. This prototype was already sold to 3 customers in spite of the fact that it only implements a small subset of the final set of capabilities and in spite of the fact that these customers already had access to the software products offered by our competition. PUBLIC HEALTH RELEVANCE: The benefits of the proposed research are expected to impact a number of research areas spanning from cancer, to obesity, to aging as well as any other life science area in which high-throughput methods (e.g. DNA microarrays, protein microarrays, metabolomics, etc.) are used. The biological user community that can benefit from this research includes any life science researcher using such high-throughput methods in any biological domain and any organism, from yeast, to fruit fly, to mouse, to human.