Sarkar Indra Neil
Center for Clinical & Translational Science, Department of Microbiology & Molecular Genetics, and Department of Computer Science, University of Vermont, Burlington, VT.
AMIA Annu Symp Proc. 2010 Nov 13;2010:717-21.
A better understanding of commensal microbiotic communities ("microbiomes") may provide valuable insights to human health. Towards this goal, an essential step may be the development of approaches to organize data that can enable comparative hypotheses across mammalian microbiomes. The present study explores the feasibility of using existing biomedical informatics resources - especially focusing on those available at the National Center for Biomedical Ontology - to organize microbiome data contained within large sequence repositories, such as GenBank. The results indicate that the Foundational Model of Anatomy and SNOMED CT can be used to organize greater than 90% of the bacterial organisms associated with 10 domesticated mammalian species. The promising findings suggest that the current biomedical informatics infrastructure may be used towards the organizing of microbiome data beyond humans. Furthermore, the results identify key concepts that might be organized into a semantic structure for incorporation into subsequent annotations that could facilitate comparative biomedical hypotheses pertaining to human health.
更好地理解共生微生物群落（“微生物组”）可能为人类健康提供有价值的见解。为了实现这一目标，一个关键步骤可能是开发能够组织数据的方法，以便对哺乳动物微生物组进行比较假设。本研究探讨了利用现有生物医学信息学资源——特别是关注国家生物医学本体中心提供的资源——来组织大型序列库（如GenBank）中包含的微生物组数据的可行性。结果表明，解剖学基础模型和SNOMED CT可用于组织与10种家养哺乳动物物种相关的90%以上的细菌生物体。这些有前景的发现表明，当前的生物医学信息学基础设施可用于组织人类以外的微生物组数据。此外，研究结果确定了一些关键概念，这些概念可能被组织成一种语义结构，以便纳入后续注释中，从而促进与人类健康相关的比较生物医学假设。
