Collaborative research: ABI Development: Ontology-enabled reasoning across phenotypes from evolution and model organisms

南达科他大学和北卡罗来纳大学被授予合作赠款，以开发本体论驱动的工具，用于对大量表型数据进行机器推理。人类可读的“表型”属性的描述，如解剖学和行为，不太适合计算分析。然而，在进化生物学、遗传学和发展学中，在文献和在线数据库中报告的海量描述性表型数据中发现模式是必要的计算辅助。本体是结构化的、受控的词汇表，可以应用于描述性数据的集合，以允许使用逻辑推理。使用从鳍到肢体的进化过渡作为测试系统，该项目将开发本体感知软件，允许用户在大型和多样化的数据集中发现不同分类群或突变基因的相似表型集。将开发一个快速语义相似性引擎，以允许搜索具有相似表型特征的进化过渡和突变基因。将开发一个本体论框架，用于对同源性进行推理，以允许对进化多样性谱系进行严格的推理。将开发自然语言处理工具，以提高从文献中挖掘表型数据的效率，并提高数据的一致性。这套工具将在来自不同化石和现代脊椎动物的大量骨骼表型上进行测试。脊椎动物的分类学和解剖学本体论将被扩充，解剖同源性的假设将被正式编码。本体论和软件工具，以及从脊椎动物系统文献中提取的表型，将与三种脊椎动物模式生物：斑马鱼(Danio Rerio)、非洲爪蛙(Xenopus Laevis)和小鼠(Mus Musculus)的遗传和表型数据整合在知识库中。知识库将使用语义网标准向一般推理者公开。该系统将通过成功检索脊椎动物鳍-肢转变和骨骼进化中其他重大事件的候选基因来验证。测试数据的进化广度要求开发一个严格的框架来对同源性假设进行推理。另一个目标是开发和评估自然语言处理工具，以从已出版文献中可用的描述中有效地捕获表型的本体论描述。这套工具将通过恢复脊椎动物从鳍到肢的进化转变的发育遗传路径进行验证，并通过与该项目的领域生物信息学家和来自更广泛用户社区的生物学家进行迭代测试来改进。在该项目的整个生命周期中，广大用户将参与制定社区标准和资源，以促进表型知识的互操作性和可计算性。这将通过研讨会、可用性测试会议以及与关键研究网络的协调来实现。利益相关者所有权将通过快速和公开发布各种产品来增强，我们预计这些产品对更大的生物界具有直接和持久的价值，包括用于简化数据管理和执行大规模语义相似性搜索的工具、高质量的脊椎动物分类学和解剖本体论，以及基于同源性进行推理的标准。我们将通过南达科他大学的外展活动，为学生、博士后和暑期实习生提供独特的培训环境，包括通过南达科他大学的外联活动，以及通过与芝加哥大学的Project Explore合作，为少数族裔和女性学生提供独特的培训环境。项目进展和成果将通过传统和在线学术交流渠道(包括博客帖子和邮件列表)进行传播；主要网站将在https://www.phenoscape.org/wiki/.

Collaborative grants are awarded to the University of South Dakota and the University of North Carolina to develop ontology-driven tools for machine reasoning over large volumes of phenotype data. Human-readable descriptions of "phenotypic" properties such as anatomy and behavior are not well-suited to computational analysis. Yet, in evolutionary biology, genetics and development, computational assistance is necessary to discover patterns within the enormous volumes of descriptive phenotype data that are being reported in the literature and in online databases. Ontologies are structured, controlled vocabularies that can be applied to collections of descriptive data to permit logical reasoning to be used. Using the evolutionary transition from fins to limbs as a test system, this project will develop ontologically-aware software that allows users to discover similar sets of phenotypes for different taxa or mutant genes within large and diverse datasets. A fast semantic similarity engine will be developed to allow searches for evolutionary transitions and mutant genes characterized by similar phenotypic profiles. An ontological framework for reasoning over homology will be developed to allow rigorous reasoning over evolutionary diverse lineages. Natural language processing tools will be developed to improve upon the efficiency of mining phenotype data from the literature and improving data consistency. This suite of tools will be tested on a large number of skeletal phenotypes from diverse fossil and modern vertebrates. Taxonomic and anatomical ontologies for vertebrates will be augmented and hypotheses of anatomical homology formally encoded. The ontologies and software tools, together with phenotypes extracted from the vertebrate systematic literature, will be integrated in the knowledgebase with genetic and phenotype data from three vertebrate model organisms: zebrafish (Danio rerio), African clawed frog (Xenopus laevis), and mouse (Mus musculus). The knowledge base will be exposed to generic reasoners using semantic web standards. The system will be validated by its success in retrieving candidate genes for the well-studied vertebrate fin-limb transition and other major events in skeletal evolution. The evolutionary breadth of the test data requires the development of a rigorous framework for reasoning over hypotheses of homology. Another goal is to develop and evaluate natural language processing tools for efficiently capturing ontological descriptions of phenotype from the descriptions available in the published literature. The suite of tools will be validated by recovering developmental genetic pathways that underlie the evolutionary transition from fin to limb in vertebrates, and refined by iterative testing with domain bioinformaticians on the project and biologists from the broader user community. A broad community of users will participate through the lifecycle of this project in the development of community standards and resources for the interoperability and computability of phenotypic knowledge. This will be achieved through workshops, usability testing sessions, and coordination with key research networks. Stakeholder ownership will be enhanced by rapid and open release of a variety of products that we anticipate to be of immediate and enduring value to the greater biology community, including tools for streamlining data curation and performing large-scale semantic similarity searches, high quality vertebrate taxonomy and anatomy ontologies, and standards for reasoning over homology. We will provide a unique training environment for students, postdocs and summer interns, including Native Americans through outreach at the University of South Dakota and minority and female students though a collaboration with Project Exploration at the University of Chicago. Project progress and outcomes will be disseminated through both traditional and online outlets for scholarly communication (including blog posts and mailing lists); the primary web presence will be at https://www.phenoscape.org/wiki/.