Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
Nucleic Acids Res. 2010 Jan;38(Database issue):D754-64. doi: 10.1093/nar/gkp832. Epub 2009 Oct 22.
The Gemina system (http://gemina.igs.umaryland.edu) identifies, standardizes and integrates the outbreak metadata for the breadth of NIAID category A-C viral and bacterial pathogens, thereby providing an investigative and surveillance tool describing the Who [Host], What [Disease, Symptom], When [Date], Where [Location] and How [Pathogen, Environmental Source, Reservoir, Transmission Method] for each pathogen. The Gemina database will provide a greater understanding of the interactions of viral and bacterial pathogens with their hosts and infectious diseases through in-depth literature text-mining, integrated outbreak metadata, outbreak surveillance tools, extensive ontology development, metadata curation and representative genomic sequence identification and standards development. The Gemina web interface provides metadata selection and retrieval of a pathogen's; Infection Systems (Pathogen, Host, Disease, Transmission Method and Anatomy) and Incidents (Location and Date) along with a hosts Age and Gender. The Gemina system provides an integrated investigative and geospatial surveillance system connecting pathogens, pathogen products and disease anchored on the taxonomic ID of the pathogen and host to identify the breadth of hosts and diseases known for these pathogens, to identify the extent of outbreak locations, and to identify unique genomic regions with the DNA Signature Insignia Detection Tool.
Gemina 系统（http://gemina.igs.umaryland.edu）用于识别、标准化和整合 NIAID 类别 A-C 病毒和细菌病原体的暴发元数据，从而提供一个描述每个病原体的“Who[宿主]、What[疾病、症状]、When[日期]、Where[地点]和 How[病原体、环境源、宿主、传播方式]”的调查和监测工具。通过深入的文献文本挖掘、整合暴发元数据、暴发监测工具、广泛的本体开发、元数据管理以及代表性基因组序列鉴定和标准制定，Gemina 数据库将有助于深入了解病毒和细菌病原体与其宿主和传染病之间的相互作用。Gemina 网络界面提供了病原体的感染系统（病原体、宿主、疾病、传播方式和解剖学）和事件（地点和日期）的元数据选择和检索功能，以及宿主的年龄和性别。Gemina 系统提供了一个集成的调查和地理空间监测系统，通过病原体和宿主的分类学 ID 连接病原体、病原体产物和疾病，以确定这些病原体已知的宿主和疾病的范围，确定暴发地点的范围，并使用 DNA 特征标识检测工具识别具有独特基因组区域。
