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但全面的软件环境。该环境的主要目标是帮助化学家进行合成规划，并帮助生物学家使用这些研究人员熟悉的概念和工具解释筛选结果和选择分子。通过设计软件，考虑到这些研究人员，我们将提供新的分析过程和访问以前只有计算科学家才能访问的关键工具。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，并与其他软件和数据源进行互操作，这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。易于使用的多样性分析，合成试剂的选择，并确定相关的测量结果的结构特征的软件，将重要的决策工具到研究界的手中，并特别有用的化学家合成分子，和生物学家选择分子，根据NIH路线图分子图书馆倡议（MLI）的目标。 我们组建了一个多学科团队，该团队具有提供此类软件的独特资格，原因有三。首先，我们在实验化学遗传学领域拥有丰富的经验，包括规划，合成，以及将化学结构与生物结果联系起来。第二，我们有开发网络支持的化学和生物信息学软件的经验。第三，我们居住在一个丰富的知识环境（哈佛和麻省理工学院的布罗德研究所），这是一个卓越的中心，在生物信息学和基因组医学，并将提供访问在软件开发过程中，以丰富的实验设计策略和数据分析方法。通过向实验者部署关键软件工具，我们将开发实际用例和接口要求，这些用例和接口要求将指导软件的进一步开发，这些软件对当前和未来的NIH路线图MLI活动至关重要。我们努力的主要目标是将化学和化学生物学的新工具与现有的基因组医学分析工具相结合，扩大化学工具的范围，使生物信息学和临床研究人员能够对公共卫生产生越来越大的影响。

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.