Text Processing and Geospatial Uncertainty for Phylogeography of Zoonotic Viruses

描述（由申请人提供）：人畜共患病毒的系统地理学研究在动物和人类之间传播的病毒的地理传播和遗传谱系，如禽流感和狂犬病。这门科学可以帮助州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在包括人类在内的各种宿主群体中的感染模式。国家生物技术信息中心（NCBI），特别是基因库，为系统地理学提供了大量可用的病毒序列数据。序列及其元数据可以下载并导入软件应用程序，生成系统地理树和用于监视的模型。然而，地理空间元数据，如主机位置，在GenBank条目中是不一致的和稀疏的，我们的初步研究表明，只有大约20%的GenBank记录包含特定的信息，如一个州内的县、镇或地区。虽然这些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，除非手工提取并链接回适当的序列。从易于计算的次要数据源（如GenBank）中缺乏精确的采样位置，增加了实现病毒迁移的准确系统地理模型的难度。我们提出了一个基础设施，通过链接文献中的相关地理空间数据来改进病毒迁移的系统地理模型。这项工作是第一次尝试使用自动提取的地理空间数据，这些数据出现在与GenBank记录相对应的期刊文章中，以增强病毒迁移的建模。我们的研究将通过以下方式扩展系统地理学和人畜共患病监测：创建一个自然语言处理（NLP）基础设施，该基础设施将提高人畜共患病病毒系统地理学地理空间数据的细节水平（目标1），使用在目标1中提取的数据开发系统地理学模型，并提供适当的生物统计模型（目标2），并评估我们的方法对系统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使用综合生物医学信息学方法的人口监测框架，包括自然语言处理、生物统计学、生物信息学和数据库设计。

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.