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

描述（由申请人提供）：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，曾经被誉为圣杯，如今已是常规。然而，到目前为止，高吞吐量的圣杯还没有实现。尽管这种高通量比较已经变得相对容易，但理解导致疾病的现象仍然具有挑战性，如果不是更大的话。信号和代谢途径是描述基因信号和生物化学反应的复杂图形，发生在生物体的各个子系统中。目前的方法旨在帮助我们理解潜在的生物现象，通过使用测量的差异来识别显著影响的途径是相当简单的。许多（如果不是全部的话）这样的方法通常将途径视为简单的基因集合，并且忽略或未充分利用这些途径的本质：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（如DNA微阵列）背景下分析基因信号和代谢途径。该方法的基本原理已经通过PI的学术网站免费提供的工具进行了测试。这些工具已有11,266个注册用户，他们已经使用并信任我们的软件。这一用户基础构成了Advaita的独特资产。我们设想的产品将具有许多独特的功能，包括：i)考虑特定基因之间的相互作用；Ii)计算一个独特的“影响因子”，表征生物体的给定子系统在给定条件下的影响程度；Iii)发现疾病和药物的作用机制；Iv)确定最佳治疗干预的潜在点；v)通过监测大量参数（基因表达水平、代谢物等）来检测生物体的质变。该产品具有以下潜力：i)通过提供更少但更好的候选药物来缩短药物开发周期；ii)帮助了解疾病和药物机制；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程序的实际数据上得到了验证（其中一些已发表，其他的在这里描述为初步结果）。该技术的可行性在超过36000次基准试验中得到了证明。该产品的商业有效性已通过实施包括上述前两个功能的原型来验证。这个原型已经卖给了3个客户，尽管它只实现了最终功能集的一小部分，尽管这些客户已经可以访问我们竞争对手提供的软件产品。

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.