Regenbase: A Searchable Database to Organize Regeneration Knowledge via Ontologie

Regenbase：通过 Ontologie 组织再生知识的可搜索数据库

• 批准号: 8365739
• 负责人: John L Bixby
• 金额: $ 60.38万
• 依托单位: UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-05-15 至 2016-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8365739
• 关键词: Afferent Neurons; Area; Axon; Back; Biological; Biological Assay; Brain; Brain Diseases; Brain Injuries; Budgets; Cancer Immunology Science; Cell Death; Cells; Cellular biology; Chemical Structure; Cicatrix; Complementary DNA; Computer software; Corticospinal Tracts; Data; Data Analyses; Data Set; Databases; Dendrites; Development; Disease; Drug Compounding; Evaluation; Family; Funding; Future; Gene Expression; Gene Expression Profile; Genes; Genomics; Goals; Growth; Healthcare Systems; Human Genome Project; Individual; Informatics; Information Systems; Injury; Investigation; Knowledge; Link; Literature; Maps; Methodology; Molecular Bank; Molecular Target; Natural regeneration; Nerve; Nerve Regeneration; Nervous System Trauma; Nervous system structure; Neurons; Neurosciences; Online Systems; Ontology; Outcome; Paper; Pattern; Peripheral Nerves; PubChem; Resources; Scientist; Screening procedure; Semantics; Societies; Solutions; Source; Speed; Spinal cord damage; Spinal cord injury; Stroke; Structure of rubrospinal tract; System; Technology; Terminology; Text; Translational Research; Traumatic Brain Injury; United States National Institutes of Health; Work; axon growth; axon regeneration; base; biomedical ontology; cell motility; computer based Semantic Analysis; data integration; data mining; drug discovery; graphical user interface; information display; information framework; injured; knockout gene; knowledge base; novel; novel therapeutics; overexpression; painful neuropathy; repaired; research study; small molecule; success; text searching; therapy development; tool; vector

DESCRIPTION (provided by applicant): This application seeks funds to develop RegenBase - a novel information system to seamlessly integrate diverse data that are produced by neuroscientists and cell biologists studying nervous system injury, disease and cell motility with other resources, such as the Neuroscience Information Framework and the BioAssay Ontology. Over the past decade the NIH has funded the development of informatics tools and ontologies to allow the integration and interrogation of the massive and diverse data sets that have been produced by the human genome project. In the area of neuroscience the most advancement have been made in the creation and annotation of large anatomical data sets that reveal patterns of gene expression and connectivity. Genesat and the BrainMaps are excellent examples and are easily searched using the Neuroscience Information Framework (NIF) portal. But it is still surprisingly difficult to search for information related to repairing the injured nrvous system. To overcome this road block it is critical to build the essential tools that allow semantic web approaches to link diverse data repositories with ontologies that allow them to be interpreted and analyzed. The success of this initiative critically relies on an effective informatcs solution to integrate the various (current and future) data types generated by neuroscientists working on nervous system injury, as well as large-scale screening efforts (such as the Molecular Libraries Probe Center Network, MLPCN) into coherent data sets and to make them accessible, interpretable, and actionable for scientists of different backgrounds and with different objectives. We propose to develop a novel knowledge-based, extensible information system of interconnected components that leverages semantic-web technologies and domain level ontologies. This system is tentatively called RegenBase (Regeneration dataBase). Tremendous progress has been made during the last decade developing semantic web technologies with the goals of formalizing knowledge, linking information across different domains, and integrating large heterogeneous data sets from diverse sources. To develop RegenBase on a fast-track with limited resources, we will leverage technologies and tools from the National Center for Biological Onotology and the recently launched BioAssay Ontology. The long-term goal of the RegenBase system is seamless "on-the fly" data integration and analysis via a semantic "Linked Data" approach that is scalable with respect to information volume and complexity. RegenBase will incorporate biomedical domain-level ontologies, including our recently developed BioAssay Ontology (BAO), to semantically associate related data types and to provide a knowledge context of the underlying experiments and screening outcomes. The overarching goal of this proposed RegenBase system is to allow bench scientists to link data and results from studies on nervous system injury and disease to data and knowledge from other domains with an emphasis on molecular targets and the small molecules that perturb their function to speed the development of novel therapeutics. PUBLIC HEALTH RELEVANCE: Public and private organizations are generating diverse data sets as they attempt to develop therapies for nervous system injury and disease. One reason therapy development is slow lies in the difficulty of collecting, analyzing and displaying information from the thousands of different experiments done on nervous system injury and interpreting it based on knowledge from other areas, such as genomics, cell biology, cancer, immunology and drug discovery. We propose to develop a novel information system that will help neuroscientists working on nerve regeneration to access and use information generated by scientists around the world.

描述（由申请人提供）：该申请寻求资金来开发RegenBase -一种新型信息系统，用于无缝集成由神经科学家和细胞生物学家研究神经系统损伤，疾病和细胞运动产生的各种数据与其他资源，如神经科学信息框架和BioAssay Ontology。在过去的十年中，NIH资助了信息学工具和本体论的开发，以整合和询问人类基因组计划产生的大量和多样化的数据集。在神经科学领域，最大的进步是在创建和注释揭示基因表达和连接模式的大型解剖数据集方面。Genesat和BrainMaps是很好的例子，使用神经科学信息框架（NIF）门户网站很容易搜索。但要搜索与修复受损神经系统相关的信息仍然令人惊讶地困难。为了克服这一障碍，关键是要建立必要的工具， 万维网方法将不同的数据储存库与允许它们被解释和分析的本体联系起来。这一举措的成功关键取决于一个有效的信息解决方案，（当前和未来）神经科学家研究神经系统损伤产生的数据类型，以及大规模筛查工作（如分子图书馆探针中心网络，MLPCN）到连贯的数据集，并使他们访问，解释，并为不同背景和不同目标的科学家可操作。我们建议开发一个新的知识为基础的，可扩展的信息系统的互联组件，利用语义网络技术和领域级本体。该系统暂时称为RegenBase（再生数据库）。在过去的十年中，语义网技术的发展取得了巨大的进步，其目标是将知识形式化，将不同领域的信息联系起来，并整合来自不同来源的大型异构数据集。为了在有限资源的情况下快速开发RegenBase，我们将利用国家生物Onotology中心和最近推出的BioAssay Ontology的技术和工具。RegenBase系统的长期目标是通过语义“关联数据”方法进行无缝的“动态”数据集成和分析，该方法在信息量和复杂性方面可扩展。RegenBase将整合生物医学领域级本体，包括我们最近开发的BioAssay Ontology（BAO），以语义关联相关数据类型，并提供基础实验和筛选结果的知识背景。这个拟议的RegenBase系统的总体目标是允许实验室科学家将神经系统损伤和疾病研究的数据和结果与其他领域的数据和知识联系起来，重点是分子靶点和干扰其功能的小分子，以加速新疗法的开发。 公共卫生相关性：公共和私人组织正在生成各种数据集，因为它们试图开发神经系统损伤和疾病的疗法。治疗发展缓慢的一个原因在于难以收集，分析和显示来自数千个不同的神经系统损伤实验的信息，并根据其他领域的知识进行解释，如基因组学，细胞生物学，癌症，免疫学和药物发现。我们建议开发一个新的信息系统，帮助神经科学家研究神经再生，以获取和使用世界各地的科学家所产生的信息。