General data-analysis tools:cCemical Diversity (RMI)

描述（由申请人提供）：我们建议为定量化学生物学研究创建一个灵活而全面的软件环境。这个环境的主要目标是帮助化学家进行合成计划，生物学家解释筛选结果和选择分子，使用这些研究人员熟悉的概念和工具。通过与这些研究人员一起设计软件，我们将提供新的分析过程和访问关键工具，这些工具以前只有计算科学家才能访问。同时，通过在化学生物学家、计算科学家、统计学家和软件架构师之间建立紧密的合作，我们将提供更高端的功能以及与其他软件和数据源的互操作性，这些将是更复杂的用户最终需要的。我们提出的信息模型和软件环境将允许实验科学家在与计算同行相同的概念框架内工作，弥合理论和实验之间的关键差距，并将每种方法的优势应用于常见问题。易于使用的软件用于多样性分析，合成试剂选择，以及与测量结果相关的结构特征的确定，将把重要的决策工具交到研究界手中，对于化学家合成分子和生物学家选择分子特别有用，根据NIH路线图分子图书馆倡议（MLI）的目标。

DESCRIPTION (provided by applicant): We propose to create a flexible but comprehensive software environment for quantitative chemical biology research. A primary goal of this environment will be to aid chemists in synthetic planning, and biologists in interpreting screening results and selecting molecules, using concepts and tools familiar to these researchers. By designing software with these researchers in mind, we will provide both novel analytical processes and access to critical tools that have previously been accessible only to computational scientists. Simultaneously, by building tight collaborations between chemical biologists, computational scientists, statisticians, and software architects, we will provide higher-end functionality and interoperability with other software and data sources that more sophisticated users will ultimately demand. Our proposed information model and software environment will allow experimental scientists to work within the same conceptual framework as their computational counterparts, bridging critical gaps between theory and experiment, and applying the strengths of each approach to common problems. Easy-to-use software for diversity analysis, synthetic reagent selection, and determination of structural features relevant to measured outcomes, will place important decision-making tools into the hands of the research community, and be especially useful for chemists synthesizing molecules, and biologists selecting molecules, pursuant to the goals of the NIH Road Map Molecular Libraries Initiative (MLI). We have assembled a multidisciplinary team that is uniquely qualified to provide such software for three reasons. First, we have considerable experience in the field of experimental chemical genetics, including planning, synthesis, and relating chemical structure to biological outcomes. Second, we have experience developing web-enabled software for both chemistry and bioinformatics. Third, we reside within a rich intellectual environment (The Broad Institute of Harvard and MIT) that is a center of excellence in bioinformatics and genomic medicine, and that will provide access during software development to a wealth of experimental design strategies and data analysis methods. By deploying key software tools to experimentalists, we will,develop practical use-cases and interface requirements that will guide further development of software central to present and future NIH Road Map MLI activities. A primary goal of our effort will be to integrate new tools for chemistry and chemical biology with existing analysis tools for genomic medicine, expanding the reach of chemistry tools to enable bioinformatics and clinical researchers to have increasing impact on public health.