Muscle Logic: New Knowledge Resource for Anatomy Enables Comprehensive Searches of the Literature on the Feeding Muscles of Mammals

BackgroundIn recent years large bibliographic databases have made much of the published literature of biology available for searches. However, the capabilities of the search engines integrated into these databases for text-based bibliographic searches are limited. To enable searches that deliver the results expected by comparative anatomists, an underlying logical structure known as an ontology is required.Development and Testing of the OntologyHere we present the Mammalian Feeding Muscle Ontology (MFMO), a multi-species ontology focused on anatomical structures that participate in feeding and other oral/pharyngeal behaviors. A unique feature of the MFMO is that a simple, computable, definition of each muscle, which includes its attachments and innervation, is true across mammals. This construction mirrors the logical foundation of comparative anatomy and permits searches using language familiar to biologists. Further, it provides a template for muscles that will be useful in extending any anatomy ontology. The MFMO is developed to support the Feeding Experiments End-User Database Project (FEED, https://feedexp.org/), a publicly-available, online repository for physiological data collected from in vivo studies of feeding (e.g., mastication, biting, swallowing) in mammals. Currently the MFMO is integrated into FEED and also into two literature-specific implementations of Textpresso, a text-mining system that facilitates powerful searches of a corpus of scientific publications. We evaluate the MFMO by asking questions that test the ability of the ontology to return appropriate answers (competency questions). We compare the results of queries of the MFMO to results from similar searches in PubMed and Google Scholar.Results and SignificanceOur tests demonstrate that the MFMO is competent to answer queries formed in the common language of comparative anatomy, but PubMed and Google Scholar are not. Overall, our results show that by incorporating anatomical ontologies into searches, an expanded and anatomically comprehensive set of results can be obtained. The broader scientific and publishing communities should consider taking up the challenge of semantically enabled search capabilities.

### 研究背景
近年来，大型书目数据库已将海量已发表的生物学文献开放检索。然而，集成于此类数据库中的文本型书目检索搜索引擎功能存在局限。若要实现比较解剖学家所期望的检索效果，需依托一种被称为本体论（ontology）的底层逻辑结构。

### 本体论的开发与测试
本文提出了哺乳动物摄食肌肉本体论（Mammalian Feeding Muscle Ontology, MFMO），这是一款聚焦于参与摄食及其他口腔/咽部行为解剖结构的多物种本体论。MFMO的独特优势在于，针对每种肌肉的简单可计算定义（包含其附着点与神经支配）在所有哺乳动物中均通用。该构建方式契合比较解剖学的逻辑基础，支持使用生物学家熟悉的专业语言开展检索。此外，它还为各类解剖学本体论的扩展提供了肌肉相关的通用模板。
MFMO专为支持摄食实验终端用户数据库项目（Feeding Experiments End-User Database Project, FEED, https://feedexp.org/）而开发，该项目是一个公开可用的在线知识库，收录了哺乳动物体内摄食相关实验（如咀嚼、咬合、吞咽）的生理学数据。目前，MFMO已集成至FEED，以及两款针对特定文献集的Textpresso（文本挖掘系统，可实现科学文献语料库的高效检索）实现版本中。我们通过提出能力问题（competency questions）来测试本体论返回恰当结果的能力，以此对MFMO进行评估，并将MFMO的检索结果与PubMed及Google Scholar中类似检索的结果进行对比。

### 结果与意义
我们的测试表明，MFMO能够应答以比较解剖学通用语言构建的检索请求，而PubMed与Google Scholar则无法实现这一点。总体而言，本研究结果显示，通过将解剖学本体论融入检索流程，可获得覆盖范围更广、解剖学维度更全面的检索结果。更广泛的科研与出版界应着手应对语义化检索能力带来的挑战。