Cornelius Rosse

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.

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.

The Foundational Model of Anatomy Ontology

Anatomy is the structure of biological organisms. The term also denotes the scientific discipline devoted to the study of anatomical entities and the structural and developmental relations that obtain among these entities during the lifespan of an organism. Anatomical entities are the independent continuants of biomedical reality on which physiological and disease processes depend, and which, in response to etiological agents, can transform themselves into pathological entities. For these reasons, hard copy and in silico information resources in virtually all fields of biology and medicine, as a rule, make extensive reference to anatomical entities. Because of the lack of a generalizable, computable representation of anatomy, developers of computable terminologies and ontologies in clinical medicine and biomedical research represented anatomy from their own more or less divergent viewpoints. The resulting heterogeneity presents a formidable impediment to correlating human anatomy not only across computational resources but also with the anatomy of model organisms used in biomedical experimentation. The Foundational Model of Anatomy (FMA) ontology is being developed to fill the need for a generalizable anatomy ontology, which can be used and adapted by any computer-based application that requires anatomical information. Moreover it is evolving into a standard reference for divergent views of anatomy and a template for representing the anatomy of animals. A distinction is made between the FMA ontology as a theory of anatomy and the implementation of this theory as the FMA artifact. In either sense of the term, the FMA is a spatial-structural ontology of the entities and relations which together form the phenotypic structure of the human organism at all biologically salient levels of granularity. Making use of explicit ontological principles and sound methods, it is designed to be understandable by human beings and navigable by computers. The FMA’s ontological structure provides for machine-based inference, enabling powerful computational tools of the future to reason with biomedical data.

Motivation and Organizational Principles for Anatomical Knowledge Representation: The Digital Anatomist Symbolic Knowledge Base

OBJECTIVE Conceptualization of the physical objects and spaces that constitute the human body at the macroscopic level of organization, specified as a machine-parseable ontology that, in its human-readable form, is comprehensible to both expert and novice users of anatomical information. DESIGN Conceived as an anatomical enhancement of the UMLS Semantic Network and Metathesaurus, the anatomical ontology was formulated by specifying defining attributes and differentia for classes and subclasses of physical anatomical entities based on their partitive and spatial relationships. The validity of the classification was assessed by instantiating the ontology for the thorax. Several transitive relationships were used for symbolically modeling aspects of the physical organization of the thorax. RESULTS By declaring Organ as the macroscopic organizational unit of the body, and defining the entities that constitute organs and higher level entities constituted by organs, all anatomical entities could be assigned to one of three top level classes (Anatomical structure, Anatomical spatial entity and Body substance). The ontology accommodates both the systemic and regional (topographical) views of anatomy, as well as diverse clinical naming conventions of anatomical entities. CONCLUSIONS The ontology formulated for the thorax is extendible to microscopic and cellular levels, as well as to other body parts, in that its classes subsume essentially all anatomical entities that constitute the body. Explicit definitions of these entities and their relationships provide the first requirement for standards in anatomical concept representation. Conceived from an anatomical viewpoint, the ontology can be generalized and mapped to other biomedical domains and problem solving tasks that require anatomical knowledge.

Small lymphocyte and transitional cell populations of the bone marrow; their role in the mediation of immune and hemopoietic progenitor cell functions.

Publisher Summary This chapter discusses the small lymphocytes and transitional cell populations of the bone marrow. Their role in the mediation of immune and hemopoietic progenitor cell function is defined. In endothermic vertebrates the bone marrow is the central organ of hemopoiesis. It is the major source of all types of cellular elements that circulate in the blood. The bone marrow plays a major role in the development of those lymphocytes that function as the precursors of antibody-forming cells. In addition, it contains small lymphocytes competent to engage in cell-mediated immune responses. Moreover, the marrow can generate such cells under various experimental conditions. Lymphocytes of the marrow have also been implicated as pluripotent hemopoietic stem cells. On the whole, modern techniques of experimental hematology have furnished evidence in support of the historic argument, and now it seems clear that hemopoietic stem cells, and progenitor cells with varying degrees of commitment to specific lines of hemopoietic differentiation, are contained in the population of bone marrow cells designated by many investigators as “lymphoid.” The chapter examines the evidence that relates various biological parameters to the functions attributed to small lymphocytes and transitional cells.

Pushing the envelope: challenges in a frame-based representation of human anatomy

One of the main threads in the history of knowledge-representation formalisms is the trade-off between the expressiveness of first-order logic on the one hand and the tractability and ease-of-use of frame-based systems on the other hand. Frame-based systems provide intuitive, cognitively easy-to-understand, and scalable means for modeling a domain. However, when a domain model is particularly complex, frame-based representation may lead to complicated and sometimes awkward solutions. We have encountered such problems when developing the Digital Anatomist Foundational Model, an ontology aimed at representing comprehensively the physical organization of the human body. We show that traditional frame-based techniques such as is-a hierarchies, slots (roles) and role restrictions are not sufficient for a comprehensive model of this domain. The diverse modeling challenges and problems in this project required us to use such knowledge-representation techniques as reified relations, metaclasses and a metaclass hierarchy, different propagation patterns for template and own slots, and so on. We posit that even though the modeling structure imposed by frame-based systems may sometimes lead to complicated solutions, it is still worthwhile to use frame-based representation for very large-scale projects such as this one.

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.

The Potential of Computerized Representations of Anatomy in the Training of Health Care Providers.

The purpose of anatomy education is to develop the skills for anatomical reasoning, which is a requirement for performing a number of clinical tasks. Anatomical reasoning integrates an understanding of the three-dimensional (3-D) geometry of the body and its parts (the spatial domain of anatomical information) with an understanding of functional, developmental, pathological, and other relationships among anatomic entities (the symbolic domain of anatomical information). Traditional methods in anatomy have substantial shortcomings for representing and integrating these two information domains. Computer-based methods of knowledge representation have a great potential for overcoming the shortcomings and for promoting anatomical reasoning. To realize this potential, there is a need for (1) establishing 3-D electronic atlases of the human body; (2) generating models of symbolic anatomical information, and (3) developing computer programs (user interfaces) that integrate these knowledge sources and serve the needs of trainees and practitioners in different fields of the health sciences. The Digital Anatomist Program at the University of Washington has begun to build such a client-server framework for anatomical information, and its application for biomedical education is being evaluated.

Terminologia Anatomica: Considered from the perspective of next‐generation knowledge sources

This report examines the semantic structure of Terminologia Anatomica, taking one page as an example. The focus of analysis is the meaning imparted to an anatomical term by virtue of its location within the structured list. Terminologias structure, expressed through hierarchies of headings, varied typographical styles, indentations, and an alphanumeric code, implies specific relationships among the terms embedded in the list. Together, terms and relationships can potentially capture essential elements of anatomical knowledge. The analysis focuses on these knowledge elements and evaluates the consistency and logic in their representation. Most critical of these elements are class inclusion and part‐whole relationships. Since these are implied, rather than explicitly modeled, by Terminologia, the use of the term list is limited to those who have some knowledge of anatomy; computer programs are excluded from navigating through the terminology. Assuring consistency in the explicit representation of anatomical relationships would facilitate adoption of Terminologia as the anatomical standard by the various controlled medical terminology (CMT) projects. These projects are motivated by the need to computerize the patient record, and their aim is to generate machine‐understandable representations of biomedical concepts, including anatomy. Because of the lack of a consistent and explicit representation of anatomy, each of these CMTs has generated its own anatomy model. None of these models is compatible with any other, yet each is consistent with textbook descriptions of anatomy. The analysis of the semantic structure of Terminologia Anatomica leads to some suggestions for enhancing the term list in ways that would facilitate its adoption as the standard for anatomical knowledge representation in biomedical informatics. Clin. Anat. 14:120–133, 2001.

The distribution of rapidly and slowly renewed T, B, and “null” lymphocytes in mouse bone marrow, thymus, lymph nodes, and spleen

Abstract Combined radioautography and immunofluorescence were employed to discern the proportions of rapidly renewed (RR) and slowly renewed (SR) T, B, and null cells in mouse lymph nodes (LN), spleen (Spl), thymus (Thy), and the lymphocyte-rich fraction of bone marrow (BML). Thy and BML were found to consist predominantly of cells with a rapid turnover rate (95.4 and 76.9%, respectively) in accord with their roles as primary lymphoid organs. In contrast, the secondary lymphoid organs were primarily composed of SR cells (LN, 73.4%; Spl, 67.8%) and contained a more even admixture of the six lymphocyte subsets. Most cells in Thy were RR T cells (93.3%), whereas the predominant lymphocyte subpopulation in both LN and Spl consisted of SR T cells (56 and 50%, respectively), with RR T cells being much less frequent (14.6% LN; 6.8% Spl). BML contained both RR and SR cells which stained with the T-cell reagent (7.8 and 7.1%). These percentages are probably overestimates, however, since this reagent stained some nonlymphoid cells in BML. RR B cells were most plentiful in BML (31.4%) and Spl (23.3%), less common in LN (11.2%), and rare in Thy (0.4%). SR B cells were equally numerous in Spl (16%), LN (15.4%), and BML (15.3%). RR null cells were the most prevalent cell type in BML (37.7%), but were infrequent in other tissues (1.6% Thy, 2.1% LN, 2.1% Spl). SR null cells were rare in all tissues (0% Thy, 2% LN, 2.1% Spl, 0.7% BML). These experiments represent the first comprehensive investigation of the composition of the lymphomyeloid organs in terms of RR and SR T, B, and null cells. They conclusively demonstrate RR and SR lymphocytes in all three functional categories (T, B, and null) and show characteristic tissue distributions of the six lymphocyte subsets.