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Animal model integration to AutDB, a genetic database for autism

机译:将动物模型集成到自闭症的遗传数据库AutDB中

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Background In the post-genomic era, multi-faceted research on complex disorders such as autism has generated diverse types of molecular information related to its pathogenesis. The rapid accumulation of putative candidate genes/loci for Autism Spectrum Disorders (ASD) and ASD-related animal models poses a major challenge for systematic analysis of their content. We previously created the Autism Database (AutDB) to provide a publicly available web portal for ongoing collection, manual annotation, and visualization of genes linked to ASD. Here, we describe the design, development, and integration of a new module within AutDB for ongoing collection and comprehensive cataloguing of ASD-related animal models. Description As with the original AutDB, all data is extracted from published, peer-reviewed scientific literature. Animal models are annotated with a new standardized vocabulary of phenotypic terms developed by our researchers which is designed to reflect the diverse clinical manifestations of ASD. The new Animal Model module is seamlessly integrated to AutDB for dissemination of diverse information related to ASD. Animal model entries within the new module are linked to corresponding candidate genes in the original "Human Gene" module of the resource, thereby allowing for cross-modal navigation between gene models and human gene studies. Although the current release of the Animal Model module is restricted to mouse models, it was designed with an expandable framework which can easily incorporate additional species and non-genetic etiological models of autism in the future. Conclusions Importantly, this modular ASD database provides a platform from which data mining, bioinformatics, and/or computational biology strategies may be adopted to develop predictive disease models that may offer further insights into the molecular underpinnings of this disorder. It also serves as a general model for disease-driven databases curating phenotypic characteristics of corresponding animal models.
机译:背景技术在后基因组时代,对自闭症等复杂疾病的多方面研究产生了与其发病机理相关的各种分子信息。自闭症谱系障碍(ASD)和与ASD相关的动物模型的推定候选基因/基因位的快速积累为对其内容进行系统分析提出了重大挑战。我们之前创建了自闭症数据库(AutDB),以提供可公开访问的Web门户网站,以进行与ASD相关的基因的持续收集,手动注释和可视化。在这里,我们描述了AutDB中新模块的设计,开发和集成,该模块用于正在进行的ASD相关动物模型的收集和全面分类。描述与原始的AutDB一样,所有数据均摘自已发表的,经过同行评审的科学文献。动物模型由我们的研究人员开发了新的表型标准词汇表,以反映ASD的多种临床表现。新的动物模型模块无缝集成到AutDB中,用于传播与ASD相关的各种信息。新模块中的动物模型条目链接到资源的原始“人类基因”模块中的相应候选基因,从而允许在基因模型和人类基因研究之间进行跨模式导航。尽管当前版本的动物模型模块仅限于小鼠模型,但其设计具有可扩展的框架,该框架可以在将来轻松合并自闭症的其他物种和非遗传病因模型。结论重要的是,该模块化ASD数据库提供了一个平台,可从该平台中采用数据挖掘,生物信息学和/或计算生物学策略来开发预测性疾病模型,从而可以进一步了解该疾病的分子基础。它也可以作为疾病驱动数据库的通用模型,用于管理相应动物模型的表型特征。

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