Collective Intelligence, Knowledge Infrastructure, & High Performance Computing

集体智慧、知识基础设施、

• 批准号: 7970400
• 负责人: calvin a johnson
• 金额: $ 294.17万
• 依托单位: CENTER FOR INFORMATION TECHNOLOGY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7970400
• 关键词: Address; Algorithms; Architecture; Biological Assay; Biological Markers; Biomedical Research; Body of uterus; Cataloging; Catalogs; Clinical; Clinical Data; Clinical Informatics; Clinical Trials; Collaborations; Communities; Complex; Computer Analysis; Data; Development; Discipline; Effectiveness; Engineering; Fostering; Genomics; Goals; Gold; High Performance Computing; Human; Imagery; Informatics; Information Resources; Information Systems; Information Technology; Intelligence; Knowledge; Linguistics; Machine Learning; Management Information Systems; Measures; Medical Imaging; Medical Records; Methodology; Methods; Molecular Bank; National Institute of Dental and Craniofacial Research; Natural Language Processing; Online Systems; Oral Diagnosis; Performance; Proteomics; Protocols documentation; Reporting; Research; Research Infrastructure; Research Personnel; Resource Sharing; Resources; Saliva; Salivary Proteins; Science; Scientist; Screening procedure; Semantics; Software Engineering; Software Tools; Strategic Planning; System; Systemic disease; Systems Biology; Technology; Text; Time; Translational Research; United States National Institutes of Health; Work; base; biological systems; cancer Biomedical Informatics Grid; cluster computing; data management; data mining; data sharing; high reward; high risk; improved; information organization; interoperability; knowledge base; programs; repository; social; success; text searching; tool

The Collective Intelligence, Knowledge Infrastructure, and High Performance Program, which operates within the High Performance Computing and Informatics Office (HPCIO), Division of Computational Bioscience of CIT, is collaborating with NIH investigators to build a critical mass in collective intelligence that is envisioned to encompass a number of pertinent and related disciplines in biomedical research including semantic interoperability, knowledge engineering, computational linguistics, text and data mining, natural language processing, machine learning, and visualization. The program is intended to foster advances in critical domains at NIH including biomedical and clinical informatics, translational research, proteomics research, genomics, systems biology, and portfolio analysis. In 2009, collaborations in support of these goals included the following. - The human salivary protein catalog has been made available online on a community-based Web portal developed by HPCIO, in collaboration with NIDCR, to enable scientists to add their own research data, share results, and discover new knowledge. This is a major step towards the discovery and use of saliva biomarkers to diagnose oral and systemic diseases. - HPCIO has developed context-sensitive text-mining methodology for identifying High-Risk, High-Reward (HRHR) research based from NIH Summary Statements. The method, which uses natural language processing to parse text and classify documents, has been successful in retrospective analysis of the most recent five-years summaries. This work is being conducted in collaboration with Division of Program Coordination, Planning, and Strategic Initiatives (DPCPSI), NIH Office of the Director (OD). - HPCIO is developing a corpus of annotated NIH medical records for use in developing methods of document de-identification. The goal is to create a gold standard that de-identification algorithms for use at NIH can be measured against. This work, in collaboration with the Clinical Center, will enhance the availability of medical records stored within the Biomedical Translational Research Information System. - HPCIO is working with the caBIG Clinical Trial Management System Workspace (in collaboration with NCI) to develop a Protocol Lifecycle Tracking (PLT) tool. By providing real-time protocol status information on all relevant trials to clinicians and researchers, bottlenecks and latencies in protocol management can be identified and corrected by those responsible for conduct of a trail and the overall success of a clinical trial program. - As a component of the Molecular Libraries Roadmap imitative, the Common Assay Reporting System (CARS) allows investigators and program directors to track the status of assay projects related information at each screening center within the Molecular Libraries Program Center Network (MLPCN). The system also provides a means for collecting, sharing and retrieving of bioassay information among the centers and program office at NIH. - HPCIO is initiating a pilot endeavor with NCI to develop deep knowledge bases representing NCIs scientific portfolio. The pilot will explore several different representation paradigms (which store not only scientific concepts but the relationships between concepts as well) to evaluate their effectiveness at various tasks including document categorization, clustering, and visualization. A similar collaboration has recently been initiated with DPCPSI/OD.

集体智能，知识基础设施和高性能计划， CIT的计算生物科学划分的高性能计算和信息学办公室（HPCIO）的运营正在与NIH研究人员合作，以在集体智能中建立关键的质量，这些智能旨在涵盖许多相关且相关的生物医学研究中的相关训练，包括语义互操作性，知识工程学，计算语言语言学，文本和自然数据，自然，自然，机器，机器，机器，机器，机器，机器，机器，计算语言化，机器，自然，来源，计算语言，机器，自然，机器，机器，机器，机器，机器，机器，机器，机器。 该计划旨在促进NIH关键领域的进步，包括生物医学和临床信息学，转化研究，蛋白质组学研究，基因组学，系统生物学和投资组合分析。 2009年，支持这些目标的合作包括以下内容。 - 人类唾液蛋白目录已在HPCIO与NIDCR合作开发的基于社区的Web门户网站上在线提供，以使科学家能够添加自己的研究数据，共享结果并发现新知识。这是朝着发现和使用唾液生物标志物来诊断口腔和系统性疾病的主要一步。 -HPCIO开发了上下文敏感的文本挖掘方法，用于识别基于NIH摘要陈述的高风险，高奖励（HRHR）研究。 该方法使用自然语言处理来解析文本和对文档进行分类，在对最近五年摘要的回顾性分析中已经成功。 这项工作正在与计划协调，计划和战略计划（DPCPSI）的部门合作进行，NIH主任办公室（OD）。 -HPCIO正在开发带有注释的NIH病历的语料库，用于开发文件识别方法。 目的是创建一个黄金标准，可以对NIH使用识别算法进行测量。 这项工作与临床中心合作将增强生物医学转化研究信息系统中存储的医疗记录的可用性。 -HPCIO正在与Cabig临床试验管理系统工作区（与NCI合作）合作开发协议生命周期跟踪（PLT）工具。 通过向临床医生和研究人员提供有关所有相关试验的实时协议状态信息，可以通过负责进行TRAIL的人员以及临床试验计划的整体成功来确定和纠正协议管理中的瓶颈和延迟。 - 作为分子图书馆路线图模仿的组成部分，通用测定报告系统（CARS）允许研究人员和程序主管跟踪分子图书馆计划中心网络（MLPCN）内每个筛选中心的测定项目相关信息的状态。该系统还提供了一种在NIH中心和计划办公室收集，共享和检索生物测定信息的方法。 -HPCIO正在向NCI进行一项飞行员努力，以发展代表NCIS科学投资组合的深层知识基础。 飞行员将探索几种不同的表示范式（它们不仅存储了科学概念，还存储了概念之间的关系），以评估其在各种任务中的有效性，包括文档分类，聚类和可视化。 最近与DPCPSI/OD一起启动了类似的合作。