Integrative tools for protozoan parasite research

描述（由申请人提供）：我们建议研究数据表示和集成工具，以促进对原生动物寄生虫基因组生物学的理解。这些工具中的许多也将对其他病原体有用，有些将有助于提供与宿主的链接。在这项提案中，我们建立在以前的成就与apicomplexan和功能基因组数据库攻击的关键问题，可以通过数据集成和增强的数据处理来解决。为了使病原体基因组数据库、算法和工具的数据集成成为可能，我们将在开放生物医学本体（OBO）Foundry的背景下开发必要的语义（本体）。我们还将进一步开发WebProtigi，以促进协作本体构建和本体集成。利用这些语义，我们将开发新的工具，以促进原生动物和宿主（人类，小鼠和其他脊椎动物）的联系的研究，通过建立在Web服务和银河开源平台，使大规模的数据分析，而无需专门的软件开发。 公共卫生相关性：原生动物寄生虫，如那些导致疟疾和弓形虫病仍然是对全球健康的主要威胁，也是一个重要的生物防御问题。目前的治疗方法是有限的，有时会受到获得性耐药性的影响。解决方案将来自对正在进行的研究的整合和挖掘。拟议的研究将提供新的框架和工具，以促进数据集成和计算挖掘的基因组规模的数据集。

DESCRIPTION (provided by applicant): We propose research on data-representation and integration tools to advance understanding of protozoan parasite genome biology. Many of these tools will also be useful for other pathogens and some will be useful for providing links to the host. In this proposal, we build on previous accomplishments with apicomplexan and functional genomic databases to attack critical problems that can be addressed through data integration and enhanced data processing. In order to make data integration possible for pathogen genome databases, algorithms and tools, we will develop the necessary semantics (ontologies) in the context of the Open Biomedical Ontologies (OBO) Foundry. We will also further develop WebProtigi to facilitate collaborative ontology building and integration of ontologies. Taking advantage of these semantics, we will develop new tools to facilitate research on protozoan and links to hosts (human, mouse and other vertebrates), by building upon Web services and the Galaxy open source platform to enable large-scale data analysis without dedicated software development. PUBLIC HEALTH RELEVANCE: Protozoan parasites such as those that cause malaria and toxoplasmosis remain major threats to global health, and a significant biodefense concern. Current treatments are limited and sometimes compromised by acquired resistance. Solutions will come from the integration and mining of ongoing research. The proposed research will provide new frameworks and tools to facilitate data integration and computational mining of genomic-scale datasets.