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Cornelius Rosse

Publications and source records attributed to Cornelius Rosse.

18 recordsLinked to original sources

A formal theory for spatial representation and reasoning in biomedical ontologies.

OBJECTIVE: The objective of this paper is to demonstrate how a formal spatial theory can be used as an important tool for disambiguating the spatial information embodied in biomedical ontologies and for enhancing their automatic reasoning capabilities. METHOD AND MATERIALS: This paper presents a formal theory of parthood and location relations among individuals, called Basic Inclusion Theory (BIT). Since biomedical ontologies are comprised of assertions about classes of individuals (rather than assertions about individuals), we define parthood and location relations among classes in the extended theory Basic Inclusion Theory for Classes (BIT+Cl). We then demonstrate the usefulness of this formal theory for making the logical structure of spatial information more precise in two ontologies concerned with human anatomy: the Foundational Model of Anatomy (FMA) and GALEN. RESULTS: We find that in both the FMA and GALEN, class-level spatial relations with different logical properties are not always explicitly distinguished. As a result, the spatial information included in these biomedical ontologies is often ambiguous and the possibilities for implementing consistent automatic reasoning within or across ontologies are limited. CONCLUSION: Precise formal characterizations of all spatial relations assumed by a biomedical ontology are necessary to ensure that the information embodied in the ontology can be fully and coherently utilized in a computational environment. This paper can be seen as an important beginning step toward achieving this goal, but much more work along these lines is required.

Anatomy↗

Relations in biomedical ontologies.

To enhance the treatment of relations in biomedical ontologies we advance a methodology for providing consistent and unambiguous formal definitions of the relational expressions used in such ontologies in a way designed to assist developers and users in avoiding errors in coding and annotation. The resulting Relation Ontology can promote interoperability of ontologies and support new types of automated reasoning about the spatial and temporal dimensions of biological and medical phenomena.

Biomedical Research↗

Processes and problems in the formative evaluation of an interface to the Foundational Model of Anatomy knowledge base.

The Digital Anatomist Foundational Model of Anatomy (FMA) is a large semantic network of more than 100,000 terms that refer to the anatomical entities, which together with 1.6 million structural relationships symbolically represent the physical organization of the human body. Evaluation of such a large knowledge base by domain experts is challenging because of the sheer size of the resource and the need to evaluate not just classes but also relationships. To meet this challenge, the authors have developed a relation-centric query interface, called Emily, that is able to query the entire range of classes and relationships in the FMA, yet is simple to use by a domain expert. Formative evaluation of this interface considered the ability of Emily to formulate queries based on standard anatomy examination questions, as well as the processing speed of the query engine. Results show that Emily is able to express 90% of the examination questions submitted to it and that processing time is generally 1 second or less, but can be much longer for complex queries. These results suggest that Emily will be a very useful tool, not only for evaluating the FMA, but also for querying and evaluating other large semantic networks.

Anatomy↗

Evolution of a Foundational Model of Physiology: symbolic representation for functional bioinformatics.

We describe the need for a Foundational Model of Physiology (FMP) as a reference ontology for "functional bioinformatics". The FMP is intended to support symbolic lookup, logical inference and mathematical analysis by integrating descriptive, qualitative and quantitative functional knowledge. The FMP will serve as a symbolic representation of biological functions initially pertaining to human physiology and ultimately extensible to other species. We describe the evolving architecture of the FMP, which is based on the ontological principles of the BioD biological description language and the Foundational Model of Anatomy (FMA).

Computational Biology↗

A relation-centric query engine for the Foundational Model of Anatomy.

The Foundational Model of Anatomy (FMA), a detailed representation of the structural organization of the human body, was constructed to support the development of software applications requiring knowledge of anatomy. The FMA's focus on the structural relationships between anatomical entities distinguishes it from other current anatomical knowledge sources. We developed Emily, a query engine for the FMA, to enable users to explore the richness and depth of these relationships. Preliminary analysis suggests that Emily is capable of correctly processing real world anatomical queries provided they have been translated into a constrained form suitable for processing by the query engine.

Anatomy↗

Problems and solutions with integrating terminologies into evolving knowledge bases.

We have merged two established anatomical terminologies with an evolving ontology of biological structure: the Foundational Model of Anatomy. We describe the problems we have encountered and the solutions we have developed. We believe that both the problems and solutions generalize to the integration of any legacy terminology with a disciplined ontology within the same domain.

Anatomy↗

The role of foundational relations in the alignment of biomedical ontologies.

The Foundational Model of Anatomy (FMA) symbolically represents the structural organization of the human body from the macromolecular to the macroscopic levels, with the goal of providing a robust and consistent scheme for classifying anatomical entities on the basis of explicit definitions. This scheme also provides a template for modeling pathology, physiological function and genotype-phenotype correlations, and it can thus serve as a reference ontology in biomedical informatics. Here we articulate the need for formally clarifying the is-a and part-of relations in the FMA and similar ontology and terminology systems. We diagnose certain characteristic errors in the treatment of these relations and show how these errors can be avoided through adoption of the formalism we describe. We then illustrate how a consistently applied formal treatment of taxonomy and partonomy can support the alignment of ontologies.

Anatomy↗

OQAFMA Querying agent for the Foundational Model of Anatomy: a prototype for providing flexible and efficient access to large semantic networks.

The development of large semantic networks, such as the UMLS, which are intended to support a variety of applications, requires a flexible and efficient query interface for the extraction of information. Using one of the source vocabularies of UMLS as a test bed, we have developed such a prototype query interface. We first identify common classes of queries needed by applications that access these semantic networks. Next, we survey StruQL, an existing query language that we adopted, which supports all of these classes of queries. We then describe the OQAFMA Querying Agent for the Foundational Model of Anatomy (OQAFMA), which provides an efficient implementation of a subset of StruQL by pre-computing a variety of indices. We describe how OQAFMA leverages database optimization by converting StruQL queries to SQL. We evaluate the flexibility and efficiency of our implementation using English queries written by anatomists. This evaluation verifies that OQAFMA provides flexible, efficient access to one such large semantic network, the Foundational Model of Anatomy, and suggests that OQAFMA could be an efficient query interface to other large biomedical knowledge bases, such as the Unified Medical Language System.

Abstracting and Indexing↗

A reference ontology for biomedical informatics: the Foundational Model of Anatomy.

The Foundational Model of Anatomy (FMA), initially developed as an enhancement of the anatomical content of UMLS, is a domain ontology of the concepts and relationships that pertain to the structural organization of the human body. It encompasses the material objects from the molecular to the macroscopic levels that constitute the body and associates with them non-material entities (spaces, surfaces, lines, and points) required for describing structural relationships. The disciplined modeling approach employed for the development of the FMA relies on a set of declared principles, high level schemes, Aristotelian definitions and a frame-based authoring environment. We propose the FMA as a reference ontology in biomedical informatics for correlating different views of anatomy, aligning existing and emerging ontologies in bioinformatics ontologies and providing a structure-based template for representing biological functions.

Abstracting and Indexing↗

A prototype natural language interface to a large complex knowledge base, the Foundational Model of Anatomy.

We describe a constrained natural language interface to a large knowledge base, the Foundational Model of Anatomy (FMA). The interface, called GAPP, handles simple or nested questions that can be parsed to the form, subject-relation-object, where subject or object is unknown. With the aid of domain-specific dictionaries the parsed sentence is converted to queries in the StruQL graph-searching query language, then sent to a server we developed, called OQAFMA, that queries the FMA and returns output as XML. Preliminary evaluation shows that GAPP has the potential to be used in the evaluation of the FMA by domain experts in anatomy.

Anatomy↗

Representing complexity in part-whole relationships within the Foundational Model of Anatomy.

The Foundational Model of Anatomy (FMA) is a frame-based ontology that represents declarative knowledge about the structural organization of the human body. Part-whole relationships play a particularly important role in this representation. In order to assure that knowledge-based applications relying on the FMA as a resource can reason about anatomy, we have modified and enhanced currently available schemes of meronymic relationships. We have introduced and defined distinct partitions for decomposing anatomical structures and attributed the part relationships in order to eliminate ambiguity and enhance specificity in the richness of meronymic relationships within the FMA.

Anatomy↗

An approach to the anatomical correlation of species through the Foundational Model of Anatomy.

The increasing need for extrapolating information from one species to another has been highlighted by contemporary research in bioinformatics, genomics, proteomics, and animal models of human disease, as well as other fields. We propose an approach to correlating the anatomy of Homo sapiens with selected species, using the Foundational Model of Anatomy (FMA) as a framework, and graph matching as a method, for determining similarities and differences in the nodes and relationships (edges) defined by the attributed graph of the FMA. We illustrate our approach by comparing anatomical structures of mouse and human that present prototypical mapping problems.

Anatomy↗

Proposed classification of cells in the Foundational Model of Anatomy.

A logical and principled representation of cell types and their component parts could serve as a framework for correlating the various ontologies that are emerging in bioinformatics with a focus on cells and subcellular biological entities. In order to address this need we have extended the Foundational Model of Anatomy (FMA)1,2 from macroscopic to cellular and subcellular anatomical entities. The poster will provide a live demonstration of this implementation.

Anatomy↗

Efficient web-based navigation of the Foundational Model of Anatomy.

The University of Washington's Foundational Model of Anatomy (FMA)1 is a complex, frame-based model composed of over 170,000 frames collectively specified by more than 1.4 million slot values. The Foundational Model Explorer (FME) was designed to provide simple and intuitive web access to this complex knowledge base. The Foundational Model Explorer (FME) (Figure 1) is built upon the Protégé 2000 knowledge base access library [http://protege.stanford.edu/]. The FME application, associated libraries, and the FMA database all reside on remote servers. Users of the FME are not required to download, install, or set-up any of these components. The FME application, in response to a query, retrieves the appropriate information from the FMA, formats these data into html documents, and transmits them, via the Internet, back to the client where they can be viewed from any standard web browser

Anatomy↗

The evolving neuroanatomical component of the Foundational Model of Anatomy.

In order to meet the need for an expressive ontology in neuroinformatics, we have integrated the extensive terminologies of NeuroNames and Terminologia Anatomica into the Foundational Model of Anatomy (FMA). We have enhanced the FMA to accommodate information unique to neuronal structures, such as axonal input/output relationships.

Anatomy↗

Guideline and quality indicators for development, purchase and use of controlled health vocabularies.

Developers and purchasers of controlled health terminologies require valid mechanisms for comparing terminological systems. By Controlled Health Vocabularies, we refer to terminologies and terminological systems designed to represent clinical data at a granularity consistent with the practice of today's healthcare delivery. Comprehensive criterion for the evaluation of such systems historically have been lacking and the known criteria are inconsistently applied. Although there are many papers which describe specific desirable features of a controlled health vocabulary, to date there is not a consistent guide for evaluators of terminologies to reference, which will help them compare implementations of terminological systems on an equal footing [Methods Inf. Med. 37 (1998) 394, J. Am. Med. Inform. Assoc. 5 (1998) 503]. This guideline serves to fill the gap between academic enumeration of desirable terminological characteristics and the practical implementation or rigorous evaluations which will yield comparable data regarding the quality of one or more controlled health vocabularies.

Guidelines as Topic↗

Anatomical evidence for the absence of a morphologically distinct cranial root of the accessory nerve in man.

The accessory nerve is conventionally described as having a cranial and spinal root. According to standard descriptions the cranial root (or part) is formed by rootlets that emerge from the medulla between the olive and the inferior cerebellar peduncle. These rootlets are considered to join the spinal root, travel with it briefly, then separate within the jugular foramen to become part of the vagus nerve. In 15 fresh specimens we exposed the posterior cranial fossa with a coronal cut through the foramen magnum and explored the course of each posterior medullary rootlet (PMR) arising from within the retro-olivary groove. We chose the caudal end of the olive as the landmark for the caudal end of the medulla. In all specimens every PMR that did not contribute to the glossopharyngeal nerve joined the vagus nerve at the jugular foramen. The distance between the caudal limit of the olive and the origin of the most caudal PMR that contributed to the vagus nerve ranged from 1-21 mm (mean = 8.8 mm). All rootlets that joined the accessory nerve arose caudal to the olive. The distance from the caudal limit of the olive and the most rostral accessory rootlet ranged from 1-15 mm (mean = 5.4 mm). We were unable to demonstrate any connection between the accessory and vagus nerves within the jugular foramen. Our findings indicate that the accessory nerve has no cranial root; it consists only of the structure hitherto referred to as its spinal root.

Accessory Nerve↗

WIRM: an open source toolkit for building biomedical web applications.

This article describes an innovative software toolkit that allows the creation of web applications that facilitate the acquisition, integration, and dissemination of multimedia biomedical data over the web, thereby reducing the cost of knowledge sharing. There is a lack of high-level web application development tools suitable for use by researchers, clinicians, and educators who are not skilled programmers. Our Web Interfacing Repository Manager (WIRM) is a software toolkit that reduces the complexity of building custom biomedical web applications. WIRM's visual modeling tools enable domain experts to describe the structure of their knowledge, from which WIRM automatically generates full-featured, customizable content management systems.

Anatomy↗