The RPI Exploratory Center for Cheminformatics(RMI)

RPI 化学信息学探索中心 (RMI)

• 批准号: 7032113
• 负责人: Curt Mark Breneman
• 金额: $ 37.56万
• 依托单位: RENSSELAER POLYTECHNIC INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-23 至 2007-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7032113
• 关键词: Internet; bioinformatics; chemical models; cheminformatics; computer program /software; computers; data collection methodology /evaluation; data management; information retrieval; interdisciplinary collaboration; model design /development; molecular biology

The purpose of this Exploratory Center for Cheminformatics Research (ECCR) P20 planning grant is to develop a mechanism for bringing together and stimulating collaborative pilot projects among a constantly-evolving nucleus of experts in Cheminformatics-related fields ranging from methods of encoding and capturing molecular information, to machine learning and data mining techniques, to predictive model development, validation, interpretation and utilization. In addition to these research efforts, the Center will bring together a set of domain specialists and application scientists who will serve as both data generators and end users of the knowledge provided by the molecular property models and modeling methods developed during the course of the grant. This group will also test the new Cheminformatics software that will constitute a tangible, deliverable product from this work. Ten application project modules that exemplify possible interactions between various groups and areas of expertise within the Center are presented as part of this proposal. The unifying vision behind the proposed Center is that much of what is done in each of the subdisciplines represented here can be expressed in a Cheminformatics context: The many diverse project areas can be grouped into one or more overlapping categories: "Data Generators" (those who use either theoretical or experimental methods for creating or extracting knowledge), "Machine Learning and Datamining" groups (who perform model validation, feature selection, pattern recognition, generation of potentials of mean force and knowledge-based potential work), as well as "Property-Prediction" groups (who perform chemically-aware model building, molecular property descriptor generation, Quantitative Structure-Property Relationship modeling, validation, and interpretation), and "Application" groups who utilize the information made available using the new tools and methods that are developed as part of the Center. It is our strong belief that these areas of expertise can be brought together within this Planning Grant proposal to generate something larger than the sum of the parts. The Exploratory Center will seed new interdisciplinary projects and train graduate students in these areas. Relevance: Advances in the generation, mining and analysis of chemical information is crucial to the development of new drug therapies, and to modern methods of bioinformatics and molecular medicine.

这个化学信息学研究中心（ECCR）P20的目的 规划赠款是开发一种机制，以汇集和刺激合作试点项目的构建和化学形式相关领域的专家核心之间，从编码和捕获分子信息的方法到机器学习和数据挖掘技术，到预测性的模型开发，验证，验证，解释，解释和利用。除了这些研究工作外，该中心还将汇集一系列领域专家和应用科学家，他们将既是数据生成器，又是由分子财产模型和赠款过程中开发的建模方法提供的知识的最终用户。该小组还将测试新的化学信息函数软件，该软件将构成这项工作的有形，可交付的产品。十个申请项目模块 该提案的一部分展示了该中心内部各个群体和专业知识领域之间可能的相互作用。 The unifying vision behind the proposed Center is that much of what is done in each of the subdisciplines represented here can be expressed in a Cheminformatics context: The many diverse project areas can be grouped into one or more overlapping categories: "Data Generators" (those who use either theoretical or experimental methods for creating or extracting knowledge), "Machine Learning and Datamining" groups (who perform model validation, feature selection, pattern recognition, generation of potentials of mean force以及基于知识的潜在工作）以及“财产预测”群体（他们进行化学意识到模型构建，分子属性描述符， 定量结构 - 范围关系建模，验证和解释）以及使用使用新工具和方法提供的信息的“应用程序”组，这些信息可用于中心的一部分。我们坚信这些专业领域可以在该计划赠款建议中汇集在一起​​，以产生比部分总和更大的东西。探索中心将在这些地区播种新的跨学科项目和培训研究生。 相关性：化学信息的一代，采矿和分析的进步对于新药疗法的发展以及现代生物信息学和分子医学方法至关重要。