Chemical Pattern Detection and Visualization in Biological Networks

描述(申请人提供)：虽然海量的分子生物活性数据创造了新的机会，但它也阻碍了科学家进行生物医学研究的方式，因为处理许多独立和不同种类的数据源存在固有的困难。数据输入的质量和类型往往会限制项目结果。为了改善研究结果，获得所有可用的数据和进行多种替代假设检验是必不可少的。针对经验较少的终端用户，我们将开发促进小分子/生物活性/生物医学数据领域的“跳跃”的工具，从一种潜在的解决方案引导到另一种解决方案，鼓励用户探索多个替代假设。我们将把来自多个生物活性数据库的数据整合到一个集中的系统中，其中包括PubChem、ChemBank、ChEMBL、PDSP和袋熊。我们将开发先进的化学模式识别算法，并提供基于细胞视角的可视化工具，用于全球探索化学模式与生物活动/目标之间的关系。我们将通过三个具体目标来实现这一点：1.为许多不同的数据库创建一个简单的统一界面，Carlsad(小分子生物活性数据联合注解研究库)；这些数据将协调人类、大鼠和小鼠靶标的多个来源的小分子生物活性数据。2.开发先进的化学模式检测和标注算法；我们将检测最大重叠集(MOS)和HIERS(层次脚手架)，并相应地标注卡尔斯巴德中的化学物质。3.开发了一个用于可视化和探索化学模式生物活性网络的Cytoscape插件。通过MOS/HIERS模式，用户将能够确定目标特定的化学特征(活性和选择性的决定因素)；在没有特定信号的情况下，这些模式将作为非目标和混杂生物活性预测的理由。卡尔斯巴德将在一个供科学界使用的企业平台上设计、实施和维护，存储独特的目标配体生物活性数据和化学模式。新的Cytoscape插件将与现有的核心组件和插件集成，以多学科的方式跨越化学和生物之间的桥梁。 公共卫生相关性：拟议的研究旨在通过一种创新的、基于网络的工具来挖掘大量的化学和生物数据，从而增强化学和生物研究社区的能力。它将为研究人员提供一种有效和改进的方式，以多学科的方式评估、可视化和探索小分子生物活性数据，从而提高人类健康研究的产出。

DESCRIPTION (provided by applicant): While the massive amount of molecular bioactivity data creates new opportunities, it also hinders the way scientists conduct biomedical research due to the inherent difficulty of processing many separate and heterogeneous data sources. The quality and type of data input often limits the project outcome. To improve research outcome, access to all available data and multiple alternative hypothesis testing are essential. Targeting less experienced end-users, we will develop tools that facilitate "jumps" in the small molecule / bioactivity / biomedical data area, leading from one potential solution to another, encouraging users to explore multiple, alternate hypotheses. We will integrate data from multiple bioactivity databases, including PubChem, ChemBank, ChEMBL, PDSP and WOMBAT, into one centralized system. We will develop advanced chemical pattern recognition algorithms and deliver a Cytoscape-based visualization tool for the global exploration of relationships between chemical patterns and biological activities/targets. We will achieve this via three Specific Aims: 1. Create one simple unified interface for many heterogeneous databases, CARLSBAD (Confederated Annotated Research Libraries of Small molecule Biological Activity Data); the data will reconcile small molecule bioactivity data across multiple sources for human, rat and mouse targets. 2. Develop advanced algorithms for chemical pattern detection and annotation; we will detect the Maximum Overlapping Set (MOS) and HierS (hierarchical scaffolds) and annotate chemicals in CARSLBAD accordingly. 3. Develop a Cytoscape plugin for the visualization and exploration of chemical pattern bioactivity networks. Via MOS/HierS patterns, users will be able to identify target specific chemical signatures (determinants for activity and selectivity); in the absence of specific signals, these patterns will serve as rationale for off- target and promiscuous bioactivity prediction. Storing unique target-ligand bioactivity data as well as chemical patterns, CARLSBAD will be designed, implemented and maintained on an enterprise platform for use by the scientific community. The new Cytoscape plugin will integrate with existing core components and plugins to bridge across chemistry and biology in a multi-disciplinary manner. PUBLIC HEALTH RELEVANCE: The proposed research aims to empower the chemistry and biology research community with an innovative, network-based tool for mining vast amounts of chemical and biological data. It will provide an effective and improved way for researchers to evaluate, visualize and explore small molecule bioactivity data in a multi-disciplinary manner, thus leading to improved output in human health research.