Text Processing and Geospatial Uncertainty for Phylogeography of Zoonotic Viruses

描述（由申请方提供）：人畜共患病毒的系统地理学研究可在动物和人类之间传播的病毒（如禽流感和狂犬病）的地理传播和遗传谱系。这项科学可以帮助国家公共卫生和农业机构确定在特定地理区域对病毒传播影响最大的动物宿主，病毒的迁移路径，包括其起源，以及随着时间的推移，包括人类在内的各种宿主人群的感染模式。美国国家生物技术信息中心（NCBI），特别是GenBank，提供了丰富的可用病毒序列数据的地理学。序列和它们的元数据可以被下载并导入到软件应用程序中，该软件应用程序生成用于监视的地理树和模型。然而，地理空间元数据（如主机位置）在GenBank条目中的表现不一致且稀疏，我们的初步研究显示，只有约20%的GenBank记录包含特定信息，如一个州内的县、镇或地区。虽然这一详细的地理空间信息可能包含在相应的期刊文章中，但它不能立即用于生物信息学或地理信息系统应用程序，除非手动提取并链接回适当的序列。缺乏精确的采样位置，从易于计算的二级数据源，如基因库增加了实现准确的病毒迁移的地理模型的难度。我们提出了一个基础设施，以改善病毒迁移的地理模型，从文献中链接相关的地理空间数据。这项工作代表了第一次努力使用自动提取的地理空间数据，目前在期刊文章中对应的基因库记录，以加强病毒迁移的建模。我们的研究将通过以下方式扩展生物地理学和人畜共患病监测：创建自然语言处理（NLP）基础设施，以提高人畜共患病病毒地理空间数据的详细程度（目标1），使用目标1中提取的数据和适当的生物统计模型开发地理空间模型（目标2），以及评估我们的方法对地理学和人畜共患病病毒监测的影响（目标3）。因此，这项工作将为研究人员提供一个框架，使用综合生物医学信息学方法，包括自然语言处理，生物统计学，生物信息学和数据库设计的人口监测。

DESCRIPTION (provided by applicant): Phylogeography of zoonotic viruses studies the geographical spread and genetic lineages of viruses that are transmittable between animals and humans such as avian influenza and rabies. This science can help state public health and agriculture agencies identify the animal hosts that most impact virus propagation in a particular geographic region, the migration path of the virus including its origin, and the patterns of infection in various host populations, including humans, over time. The National Center for Biotechnology Information (NCBI), specifically GenBank, provides an abundance of available viral sequence data for phylogeography. Sequences and their metadata can be downloaded and imported into software applications that generate phylogeographic trees and models for surveillance. However, geospatial metadata such as host location is inconsistently represented and sparse across GenBank entries, with our preliminary studies showing only about 20% of the GenBank records contain specific information such as a county, town, or region within a state. While this detailed geospatial information might be included in the corresponding journal article, it is not available for immediate use in a bioinformatics or GIS application unless it is manually extracted and linked back to the appropriate sequence. Absence of precise sampling locations from easily-computable secondary data sources such as GenBank increases the difficulty of achieving accurate phylogeographic models of virus migration. We propose an infrastructure to improve phylogeographic models of virus migration by linking relevant geospatial data from the literature. This work represents the first effort to use automatically extracted geospatial data present in journal articles corresponding to GenBank records in order to enhance modeling of virus migration. Our research will extend phylogeography and zoonotic surveillance by: creating a Natural Language Processing (NLP) infrastructure that will improve the level of detail of geospatial data for phylogeography of zoonotic viruses (Aim 1), develop phylogeographic models using the data extracted in Aim 1 with adequate biostatistical models (Aim 2), and evaluating the impact of our approach for phylogeography and surveillance of zoonotic viruses (Aim 3). Thus, this work will provide researchers with a framework for population surveillance using an integrated biomedical informatics approach including NLP, biostatistics, bioinformatics, and database design.