Representing default knowledge in biomedical ontologies: application to the integration of anatomy and phenotype ontologies

Background  

Current efforts within the biomedical ontology community focus on achieving interoperability between various biomedical ontologies that cover a range of diverse domains. Achieving this interoperability will contribute to the creation of a rich knowledge base that can be used for querying, as well as generating and testing novel hypotheses. The OBO Foundry principles, as applied to a number of biomedical ontologies, are designed to facilitate this interoperability. However, semantic extensions are required to meet the OBO Foundry interoperability goals. Inconsistencies may arise when ontologies of properties – mostly phenotype ontologies – are combined with ontologies taking a canonical view of a domain – such as many anatomical ontologies. Currently, there is no support for a correct and consistent integration of such ontologies.     

Advancing science through mining libraries, ontologies, and communities

Life scientists today cannot hope to read everything relevant to their research. Emerging text-mining tools can help by identifying topics and distilling statements from books and articles with increased accuracy. Researchers often organize these statements into ontologies, consistent systems of reality claims. Like scientific thinking and interchange, however, text-mined information (even when accurately captured) is complex, redundant, sometimes incoherent, and often contradictory: it is rooted in a mixture of only partially consistent ontologies. We review work that models scientific reason and suggest how computational reasoning across ontologies and the broader distribution of textual statements can assess the certainty of statements and the process by which statements become certain. With the emergence of digitized data regarding networks of scientific authorship, institutions, and resources, we explore the possibility of accounting for social dependences and cultural biases in reasoning models. Computational reasoning is starting to fill out ontologies and flag internal inconsistencies in several areas of bioscience. In the not too distant future, scientists may be able to use statements and rich models of the processes that produced them to identify underexplored areas, resurrect forgotten findings and ideas, deconvolute the spaghetti of underlying ontologies, and synthesize novel knowledge and hypotheses.     

The qualitative and time-dependent character of spatial relations in biomedical ontologies

MOTIVATION: The formal representation of mereological aspects of canonical anatomy (parthood relations) is relatively well understood. The formal representation of other aspects of canonical anatomy, such as connectedness and adjacency relations between anatomical parts, their shape and size as well as the spatial arrangement of anatomical parts within larger anatomical structures are, however, much less well understood and represented in existing computational anatomical and bio-medical ontologies only insufficiently. RESULTS: In this article, we provide a methodology of how to incorporate this kind of information into anatomical and bio-medical ontologies by applying techniques of representing qualitative spatial information from Artificial Intelligence. In particular, we focus on how to explicitly take into account the qualitative and time-dependent character of these relations. As a running example, we use the human temporomandibular joint (TMJ). AVAILABILITY: Using the presented methodology, a formal ontology was developed which is accessible on http://www.ifomis.org/bfo/fol. This ontology may help to improve the logical and ontological rigor of bio-medical ontologies such as the OBO relation ontology.     

Fostering critical thinking, reasoning, and argumentation skills through bioethics education

Developing a position on a socio-scientific issue and defending it using a well-reasoned justification involves complex cognitive skills that are challenging to both teach and assess. Our work centers on instructional strategies for fostering critical thinking skills in high school students using bioethical case studies, decision-making frameworks, and structured analysis tools to scaffold student argumentation. In this study, we examined the effects of our teacher professional development and curricular materials on the ability of high school students to analyze a bioethical case study and develop a strong position. We focused on student ability to identify an ethical question, consider stakeholders and their values, incorporate relevant scientific facts and content, address ethical principles, and consider the strengths and weaknesses of alternate solutions. 431 students and 12 teachers participated in a research study using teacher cohorts for comparison purposes. The first cohort received professional development and used the curriculum with their students; the second did not receive professional development until after their participation in the study and did not use the curriculum. In order to assess the acquisition of higher-order justification skills, students were asked to analyze a case study and develop a well-reasoned written position. We evaluated statements using a scoring rubric and found highly significant differences (p<0.001) between students exposed to the curriculum strategies and those who were not. Students also showed highly significant gains (p<0.001) in self-reported interest in science content, ability to analyze socio-scientific issues, awareness of ethical issues, ability to listen to and discuss viewpoints different from their own, and understanding of the relationship between science and society. Our results demonstrate that incorporating ethical dilemmas into the classroom is one strategy for increasing student motivation and engagement with science content, while promoting reasoning and justification skills that help prepare an informed citizenry.     

Phenotype ontologies: the bridge between genomics and evolution

Understanding the developmental and genetic underpinnings of particular evolutionary changes has been hindered by inadequate databases of evolutionary anatomy and by the lack of a computational approach to identify underlying candidate genes and regulators. By contrast, model organism studies have been enhanced by ontologies shared among genomic databases. Here, we suggest that evolutionary and genomics databases can be developed to exchange and use information through shared phenotype and anatomy ontologies. This would facilitate computing on evolutionary questions pertaining to the genetic basis of evolutionary change, the genetic and developmental bases of correlated characters and independent evolution, biomedical parallels to evolutionary change, and the ecological and paleontological correlates of particular types of change in genes, gene networks and developmental pathways.     

Encountering nature through fieldwork: expert knowledge,modes of reasoning,and local creativity

The concept of ‘relation’ has been central to the anthropological reworking of the nature/culture and nature/society dichotomies. However, ecology is relational in a way that has often been ignored or dismissed in contemporary socio‐cultural anthropology. This article shows that there is more to ethnoecology than an ethnocentric form of analysis representing other people's understandings of the natural world through the prejudiced lens of Western scientific classifications. Three ‘fieldwork on fieldwork’ experiments involving encounters between natural scientists and indigenous communities in Amazonian Ecuador and Southern Guyana are discussed to illustrate the heterogeneity of human knowledge, the role of expert knowledge in intercultural communication, and the need to differentiate ecological reasoning from moral reasoning.     

Exploring and linking biomedical resources through multidimensional semantic spaces

BACKGROUND: The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes). RESULTS: This paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource. CONCLUSIONS: Current knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations can be exploited for integration, exploration, and analysis tasks. Results over a real scenario demonstrate the viability and usefulness of the approach, as well as the quality of the generated multidimensional semantic spaces.     

Literature mining, ontologies and information visualization for drug repurposing

The immense growth of MEDLINE coupled with the realization that a vast amount of biomedical knowledge is recorded in free-text format, has led to the appearance of a large number of literature mining techniques aiming to extract biomedical terms and their inter-relations from the scientific literature. Ontologies have been extensively utilized in the biomedical domain either as controlled vocabularies or to provide the framework for mapping relations between concepts in biology and medicine. Literature-based approaches and ontologies have been used in the past for the purpose of hypothesis generation in connection with drug discovery. Here, we review the application of literature mining and ontology modeling and traversal to the area of drug repurposing (DR). In recent years, DR has emerged as a noteworthy alternative to the traditional drug development process, in response to the decreased productivity of the biopharmaceutical industry. Thus, systematic approaches to DR have been developed, involving a variety of in silico, genomic and high-throughput screening technologies. Attempts to integrate literature mining with other types of data arising from the use of these technologies as well as visualization tools assisting in the discovery of novel associations between existing drugs and new indications will also be presented.     

CRAVE: a database, middleware and visualization system for phenotype ontologies

MOTIVATION: A major challenge in modern biology is to link genome sequence information to organismal function. In many organisms this is being done by characterizing phenotypes resulting from mutations. Efficiently expressing phenotypic information requires combinatorial use of ontologies. However tools are not currently available to visualize combinations of ontologies. Here we describe CRAVE (Concept Relation Assay Value Explorer), a package allowing storage, active updating and visualization of multiple ontologies. RESULTS: CRAVE is a web-accessible JAVA application that accesses an underlying MySQL database of ontologies via a JAVA persistent middleware layer (Chameleon). This maps the database tables into discrete JAVA classes and creates memory resident, interlinked objects corresponding to the ontology data. These JAVA objects are accessed via calls through the middleware's application programming interface. CRAVE allows simultaneous display and linking of multiple ontologies and searching using Boolean and advanced searches.     

The relationship between cumulus cell-oocyte coupling,oocyte meiotic maturation,and cumulus expansion

The timing of the reduction of cumulus cell-oocyte coupling was correlated with oocyte meiotic maturation and the expansion (mucification) of the cumulus oophorus using immature mice treated with gonadotropins. Three hours after the injection of an ovulatory dose of human chorionic gonadotropin (hCG), more than 90% of the oocytes isolated from large Graafian follicles had undergone germinal vesicle breakdown, indicating that oocyte meiotic maturation had been initiated. However, no cumulus expansion or reduction of intercellular coupling was detected at this time. By 6 hr after hCG injection, the index of oocyte-cumulus cell coupling was still not less than that found in oocyte-cumulus cell complexes isolated from control mice not receiving hCG. Cumulus expansion at 6 hr post-hCG was limited to the outer cumulus cells while those adjacent to the oocyte were still tightly packed. Cumulus expansion appeared complete by 9 hr after hCG injection and the cumulus cell-oocyte coupling index was greatly reduced. These results show that oocyte meiotic maturation in the mouse is not initiated by a reduction in cumulus cell-oocyte coupling or by cumulus expansion. However, the results suggest that the reduction of intercellular coupling in vivo may be a result of cumulus expansion.