There is a need recognized by the National Institute of Dental & Craniofacial Research and the National Cancer Institute to advance basic, translational and clinical saliva research. The goal of the Salivaomics Knowledge Base (SKB) is to create a data management system and web resource constructed to support human salivaomics research. To maximize the utility of the SKB for retrieval, integration and analysis of data, we have developed the Saliva Ontology and SDxMart. This article reviews the informatics advances in saliva (...) diagnostics made possible by the Saliva Ontology and SDxMart. (shrink)

The automatic integration of information resources in the life sciences is one of the most challenging goals facing biomedical informatics today. Controlled vocabularies have played an important role in realizing this goal, by making it possible to draw together information from heterogeneous sources secure in the knowledge that the same terms will also represent the same entities on all occasions of use. One of the most impressive achievements in this regard is the Gene Ontology (GO), which is rapidly acquiring the (...) status of a de facto standard in the field of gene and gene product annotations, and whose methodology has been much intimated in attempts to develop controlled vocabularies for shared use in different domains of biology. The GO Consortium has recognized, however, that its controlled vocabulary as currently constituted is marked by several problematic features - features which are characteristic of much recent work in bioinformatics and which are destined to raise increasingly serious obstacles to the automatic integration of biomedical information in the future. Here, we survey some of these problematic features, focusing especially on issues of compositionality and syntactic regimentation. (shrink)

Two senses of ‘ontology’ can be distinguished in the current literature. First is the sense favored by information scientists, who view ontologies as software implementations designed to capture in some formal way the consensus conceptualization shared by those working on information systems or databases in a given domain. [Gruber 1993] Second is the sense favored by philosophers, who regard ontologies as theories of different types of entities (objects, processes, relations, functions) [Smith 2003]. Where information systems ontologists seek to maximize reasoning (...) efficiency even at the price of simplifications on the side of representation, philosophical ontologists argue that representational adequacy can bring benefits for the stability and resistance to error of an ontological framework and also for its extendibility in the future. In bioinformatics, however, a third sense of ‘ontology’ has established itself, above all as a result of the successes of the Gene Ontology (hereafter: GO), which is a tool for the representation and processing of information about gene products and their biological functions [Gene Ontology Consortium 2000]. We show how Basic Formal Ontology (BFO) has established itself as an overarching ontology drawing on all three of the strands distinguished above, and describe applications of BFO especially in the treatment of biological granularity. (shrink)

Recent work on the quality assurance of the Gene Ontology (GO, Gene Ontology Consortium 2004) from the perspective of both linguistic and ontological organization has made it clear that GO lacks the kind of formalism needed to support logic-based reasoning. At the same time it is no less clear that GO has proven itself to be an excellent terminological resource that can serve to combine together a variety of biomedical database and information systems. Given the strengths of GO, it is (...) worth investigating whether, by overcoming some of its weaknesses from the point of view of formal-ontological principles, we might not be able to enhance a version of GO which can come even closer to serving the needs of the various communities of biomedical researchers and practitioners. It is accepted that clinical and bioinformatics need to find common ground if the results of data-intensive biomedical research are to be harvested to the full. It is also widely accepted that no single method will be sufficient to create the needed common framework. We believe that the principles-based approach to life-science data integration and knowledge representation must be one of the methods applied. Indeed in dealing with the ontological representation of carcinomas, and specifically of colon carcinomas, we have established that, had GO (and related biomedical ontologies) followed some of the basic formal-ontological principles we have identified (Smith et al. 2004, Ceusters et al. 2004), then the effort required to navigate successfully between clinical and bioinformatics systems would have been reduced. We point here to the sources of ontologically-related errors in GO, and also provide arguments as to why and how such errors need to be resolved. (shrink)

Bioinformatics scientists often describe their own scientific activities as the practice of working with large amounts of data using computing devices. An essential part of their self-identification is also the development of ways to visually represent the results of this work. Some of these methods are aimed at building convenient representations of data and demonstrating patterns present in them (graphics, diagrams, graphs). Others are ways of visualizing objects that are not directly accessible to human perception (microphotography, X-ray). Both the (...) construction of visualizations and (especially) the creation of new computer visualization methods are considered in bioinformatics as significant scientific achievements. Representations of the three-dimensional structure of protein molecules play a special role in the inquiries of bioinformatics scientists. 3D-visualization of a macromolecule, on the one hand, is, like a graph, a representation of the results of computer processing of data arrays obtained by material methods – spatiotemporal coordinates of structural elements of the molecule. On the other hand, like microphotography, these 3D structures should serve as accurate representations of specific scientific objects. This leads to the parallel existence of two contradictory epistemic regimes: creative arbitrariness in making convenient, communicatively successful models, is combined with commitment to the object “as it really is”. The paradox is reinforced by the fact that the scientific study of objects in question (determining the properties of the structure, its functions, comparison with other structures) by means of computers does not require visualization at all. Its obviously high value for bioinformatics does not look justified if we take into account the prominent artificiality and artistry of the resulting images. However, the status of these images becomes clearer if we relate them to earlier notions of the role of the visual in scientific discovery. The highest estimation of visualization as the final result of scientific research was characteristic of Renaissance science. The artistic representation of ideal essential properties, instead of a strict correspondence to a particular biological object, is an epistemic virtue typical of the naturalists of the 17th and 18th centuries. Both suggested a close collaboration between the scientist and the artist; and standards for visualizing macromolecules in bioinformatics grow out of a similar collaboration (Geis’ drawings). The desire for maximum accuracy and detail inherits the regulation of “mechanical objectivity” (as Daston and Galison put it into words), for which it is also important to eliminate humans from the image production process (in bioinformatics, to transfer these functions to computer programs). Thus, 3D-visualization of protein structures bears traces of historically different value orientations, but the scientific practice of the 20th and 21st centuries, supplemented by computer technologies, allows them to be intertwined in particular disciplinary units. (shrink)

There are a number of existing classifications and staging schemes for carcinomas, one of the most frequently used being the TNM classification. Such classifications represent classes of entities which exist at various anatomical levels of granularity. We argue that in order to apply such representations to the Electronic Health Records one needs sound ontologies which take into consideration the diversity of the domains which are involved in clinical bioinformatics. Here we outline a formal theory for addressing these issues in (...) a way that the ontologies can be used to support inferences relating to entities which exist at different anatomical levels of granularity. Our case study is the colon carcinoma, one of the most common carcinomas prevalent within the European population. (shrink)

Ontological principles are needed in order to bridge the gap between medical and biological information in a robust and computable fashion. This is essential in order to draw inferences across the levels of granularity which span medicine and biology, an example of which include the understanding of the roles of tumor markers in the development and progress of carcinoma. Such information integration is also important for the integration of genomics information with the information contained in the electronic patient records in (...) such a way that real time conclusions can be drawn. In this paper we describe a large multi-granular datasource built by using ontological principles and focusing on the case of colon carcinoma. (shrink)

The integration of information resources in the life sciences is one of the most challenging problems facing bioinformatics today. We describe how Language and Computing nv, originally a developer of ontology-based natural language understanding systems for the healthcare domain, is developing a framework for the integration of structured data with unstructured information contained in natural language texts. L&C’s LinkSuite™ combines the flexibility of a modular software architecture with an ontology based on rigorous philosophical and logical principles that is designed (...) to comprehend the basic formal relationships that structure both reality and the ways humans perceive and communicate about reality. (shrink)

As part of a series of workshops on different aspects of biomedical ontology sponsored by the National Center for Biomedical Ontology (NCBO), a workshop titled "Ontologies of Cellular Networks" took place in Newark, New Jersey, on 27 to 28 March 2008. This workshop included more than 30 participants from various backgrounds in biomedicine and bioinformatics. The goal of the workshop was to provide an introduction to the basic tools and methods of ontology, as well as to enhance coordination between (...) groups already working on ontologies of cellular networks. The meeting focused on three questions: What is an ontology? What is a pathway? What is a cellular network? (shrink)

Abstract for Descent and Logic in Biosystematics: An Essay AUTHOR: THOMAS MCCABE PUBLISHER: PERSEVERANT PUBLISHING Descent and Logic in Biosystematics: An Essay is a short book about biological systematics and taxonomy. Some of the subjects con- sidered in it are philosophical: taxonomic theory, species concepts, speciation models, and evolutionary theories. Yet the book also covers matters not philosophical, such as taxonomic operations, experi- mental taxonomy, and a new suggested taxonomic method with worked examples. The author finds relationships among these topics. (...) The book is addressed to biosystematists, practicing biological tax- onomists, and philosophers of biology. It will also interest others who draw on biological taxonomy and biosystematics in their work. Descent and Logic in Biosystematics: An Essay goes into some old topics such as traditional biological identifying, classifying, and nomenclature; some recent, such as cladistic analysis, phylogenetics, and phylogenomics; and a few new, such as the logic of mutually exclusive taxon definitions, and techniques for using directly obser- ved reproductive events and pedigree analysis to untangle certain taxonomic dilemmas. There is a chapter about minimizing am- biguities when defining biological taxa, a chapter on the relevance of human biology to biosystematics, chapters addressing some biosys- tematic problems associated with the phenomenon of hybridization, a chapter on the relationship of biological taxonomy to conservation biology, and a chapter about the scientificity of evolutionary theories. Descent and Logic in Biosystematics: An Essay is published with a glossary, twelve black and white line figures, a dynamic table of contents, linked cross references, linked bibliographic citations, and a detailed index in the print and PDF versions. Descent and Logic in Biosystematics: An Essay, is available from the publisher in print and PDF formats, and from distributors and retailers as an ebook. It should be considered for academic libraries, research libraries, natural history museum libraries, the libraries of conservation organizations, and some private libraries. (shrink)

The computational genomics community has come increasingly to rely on the methodology of creating annotations of scientific literature using terms from controlled structured vocabularies such as the Gene Ontology (GO). We here address the question of what such annotations signify and of how they are created by working biologists. Our goal is to promote a better understanding of how the results of experiments are captured in annotations in the hope that this will lead to better representations of biological reality through (...) both the annotation process and ontology development, and in more informed use of the GO resources by experimental scientists. (shrink)

This paper presents an analysis of Seneca's 58th letter to Lucilius and Porphyry's Isagoge, which were the origin of the tree diagrams that became popular in philosophy and logic from the early Middle Ages onwards. These diagrams visualise the extent to which a concept can be understood as a category, genus, species or individual and what the method of dihairesis (division) means. The paper explores the dissimilarities between Seneca's and Porphyry's tree structures, scrutinising them through the perspective of modern graph (...) theory. Although traditional trees can be interpreted in a modern way, their terms and definitions defy modern standardisation. These distinctions are not only useful for differentiating between Seneca's and Porphyry's trees, but also for comprehending the evolution of this philosophical tradition. Thus the paper highlights the continued significance of these tree diagrams in analysing concepts and categories in philosophy and structuring objects and information in modern fields such as artificial intelligence, computer science, bioinformatics, graph theory, and many more. (shrink)

Ontology as a branch of philosophy is the science of what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality. ‘Ontology’ in this sense is often used by philosophers as a synonym of ‘metaphysics’ (a label meaning literally: ‘what comes after the Physics’), a term used by early students of Aristotle to refer to what Aristotle himself called ‘first philosophy’. But in recent years, in a development hardly noticed by philosophers, the (...) term ‘ontology’ has gained currency in the field of computer and information science, and in information-driven research in bioinformatics and related areas. We examine these new developments in applied ontology, and show what lessons they might have for both philosophers and information scientists. (shrink)

Background: Ontologies and taxonomies are among the most important computational resources for molecular biology and bioinformatics. A series of recent papers has shown that the Gene Ontology (GO), the most prominent taxonomic resource in these fields, is marked by flaws of certain characteristic types, which flow from a failure to address basic ontological principles. As yet, no methods have been proposed which would allow ontology curators to pinpoint flawed terms or definitions in ontologies in a systematic way. Results: We (...) present computational methods that automatically identify terms and definitions which are defined in a circular or unintelligible way. We further demonstrate the potential of these methods by applying them to isolate a subset of 6001 problematic GO terms. By automatically aligning GO with other ontologies and taxonomies we were able to propose alternative synonyms and definitions for some of these problematic terms. This allows us to demonstrate that these other resources do not contain definitions superior to those supplied by GO. Conclusion: Our methods provide reliable indications of the quality of terms and definitions in ontologies and taxonomies. Further, they are well suited to assist ontology curators in drawing their attention to those terms that are ill-defined. We have further shown the limitations of ontology mapping and alignment in assisting ontology curators in rectifying problems, thus pointing to the need for manual curation. (shrink)

The collaboration of Language and Computing nv (L&C) and the Institute for Formal Ontology and Medical Information Science (IFOMIS) is guided by the hypothesis that quality constraints on ontologies for software ap-plication purposes closely parallel the constraints salient to the design of sound philosophical theories. The extent of this parallel has been poorly appreciated in the informatics community, and it turns out that importing the benefits of phi-losophical insight and methodology into application domains yields a variety of improvements. L&C’s LinKBase® (...) is one of the world’s largest medical domain ontologies. Its current primary use pertains to natural language processing ap-plications, but it also supports intelligent navigation through a range of struc-tured medical and bioinformatics information resources, such as SNOMED-CT, Swiss-Prot, and the Gene Ontology (GO). In this report we discuss how and why philosophical methods improve both the internal coherence of LinKBase®, and its capacity to serve as a translation hub, improving the interoperability of the ontologies through which it navigates. (shrink)

Knowledge-making practices in biology are being strongly affected by the availability of data on an unprecedented scale, the insistence on systemic approaches and growing reliance on bioinformatics and digital infrastructures. What role does theory play within data-intensive science, and what does that tell us about scientific theories in general? To answer these questions, I focus on Open Biomedical Ontologies, digital classification tools that have become crucial to sharing results across research contexts in the biological and biomedical sciences, and argue (...) that they constitute an example of classificatory theory. This form of theorizing emerges from classification practices in conjunction with experimental know-how and expresses the knowledge underpinning the analysis and interpretation of data disseminated online. (shrink)

The rapidly increasing wealth of genomic data has driven the development of tools to assist in the task of representing and processing information about genes, their products and their functions. One of the most important of these tools is the Gene Ontology (GO), which is being developed in tandem with work on a variety of bioinformatics databases. An examination of the structure of GO, however, reveals a number of problems, which we believe can be resolved by taking account of (...) certain organizing principles drawn from philosophical ontology. We shall explore the results of applying such principles to GO with a view to improving GO’s consistency and coherence and thus its future applicability in the automated processing of biological data. (shrink)

We undeniably live in an information age—as, indeed, did those who lived before us. After all, as the cultural historian Robert Darnton pointed out: ‘every age was an age of information, each in its own way’ (Darnton 2000: 1). Darnton was referring to the news media, but his insight surely also applies to the sciences. The practices of acquiring, storing, labeling, organizing, retrieving, mobilizing, and integrating data about the natural world has always been an enabling aspect of scientific work. Natural (...) history and its descendant discipline of biological taxonomy are prime examples of sciences dedicated to creating and managing systems of ordering data. In some sense, the idea of biological taxonomy as an information science is commonplace. Perhaps it is because of its self-evidence that the information science perspective on taxonomy has not been a major theme in the history and philosophy of science. The botanist Vernon Heywood once pointed out that historians of biology, in their ‘preoccupation with the development of the sciences of botany and zoology… [have] diverted attention from the role of taxonomy as an information science’ (Heywood 1985: 11). More specifically, he argued that historians had failed to appreciate how principles and practices that can be traced to Linnaeus constituted ‘a change in the nature of taxonomy from a local or limited folk communication system and later a codified folk taxonomy to a formal system of information science [that] marked a watershed in the history of biology’ (ibid.). A similar observation could be made about twentieth-century philosophy of biology, which mostly skipped over practical and epistemic questions about information management in taxonomy. The taxonomic themes that featured in the emerging philosophy of biology literature in the second half of the twentieth century were predominantly metaphysical in orientation. This is illustrated by what has become known as the ‘essentialism story’: an account about the essentialist nature of pre- Darwinian taxonomy that used to be accepted by many historians and philosophers, and which stimulated efforts to document and interpret shifts in the metaphysical understanding of species and (natural) classification (Richards 2010; Winsor 2003; Wilkins 2009). Although contemporary debates in the philosophy of taxonomy have moved on, much discussion continues to focus on conceptual and metaphysical issues surrounding the nature of species and the principles of classification. Discussions centring on whether species are individuals, classes, or kinds have sprung up as predictably as perennials. Raucous debates have arisen even with the aim of accommodating the diversity of views: is monism, pluralism, or eliminativism about the species category the best position to take? In addition to these, our disciplines continue to interrogate what is the nature of these different approaches to classification: are they representational or inferential roles of different approaches to classification (evolutionary taxonomy, phenetics, phylogenetic systematics)? While there is still much to learn from these discussions—in which we both actively participate—our aim with this topical collection has been to seek different entrypoints and address underexposed themes in the history and philosophy of taxonomy. We believe that approaching taxonomy as an information science prompts new questions and can open up new philosophical vistas worth exploring. A twenty-first century information science turn in the history and philosophy of taxonomy is already underway. In scientific practice and in daily life it is hard to escape the imaginaries of Big Data and the constant threats of being ‘flooded with data’. In the life sciences, these developments are often associated with the socalled bioinformatics crisis that can hopefully be contained by a new, interdisciplinary breed of bioinformaticians. These new concepts, narratives, and developments surrounding the centrality of data and information systems in the biological and biomedical sciences have raised important philosophical questions about their challenges and implications. But historical perspectives are just as necessary to judge what makes our information age different from those that preceded us. Indeed, as the British zoologist Charles Godfray has often pointed out, the piles of data that are being generated in contemporary systematic biology have led to a second bioinformatics crisis, the first being the one that confronted Linnaeus in the mid-18th century (Godfray 2007). Although our aim is to clear a path for new discussions of taxonomy from an information science-informed point of view, we continue where others in the history, philosophy, and sociology of science have already trod. We believe that an appreciation of biological taxonomy as an information science raises many questions about the philosophical, theoretical, material, and practical aspects of the use and revision of biological nomenclatures in different local and global communities of scientists and citizen scientists. In particular, conceiving of taxonomy as an information science directs attention to the temporalities of managing an accumulating data about classified entities that are themselves subject to revision, to the means by which revision is accomplished, and to the semantic, material, and collaborative contexts that mediate the execution of revisions. (shrink)

First, I offer a short overview on the classical occidental philosophy as propounded by the ancient Greeks and the natural philosophies of the last 2000 years until the dawn of the empiricist logic of science in the twentieth century, which wanted to delimitate classical metaphysics from empirical sciences. In contrast to metaphysical concepts which didn’t reflect on the language with which they tried to explain the whole realm of entities empiricist logic of science initiated the end of metaphysical theories by (...) reflecting on the preconditions for foundation and justification of sentences about objects of investigation, i.e. a coherent definition of language in general, which was not the aim of classical metaphysics. Unexpectedly empiricist logic of science in the linguistic turn failed in the physical and mathematical reductionism of language and its use in communication, as will be discussed below in further detail. Nevertheless, such reflection on language and communication also introduced this vocabulary into biology. Manfred Eigen and bioinformatics, later on biolinguistics, used ‘language’ applied linguistic turn thinking to biology coherent to the logic of science and its formalisable aims. This changed significantly with the birth of biosemiotics and biohermeneutics. At the end of this introduction it will be outlined why and how all these approaches reproduced the deficiencies of the logic of science and why the biocommunicative approach avoids their abstractive fallacies. (shrink)

Ontology as a branch of philosophy is the science of what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality. ‘Ontology’ in this sense is often used by philosophers as a synonym of ‘metaphysics’ (a label meaning literally: ‘what comes after the Physics’), a term used by early students of Aristotle to refer to what Aristotle himself called ‘first philosophy’. But in recent years, in a development hardly noticed by philosophers, the (...) term ‘ontology’ has gained currency in the field of computer and information science, and in information-driven research in bioinformatics and related areas. We examine these new developments in applied ontology, and show what lessons they might have for both philosophers and information scientists. (shrink)

1900 was a remarkable year for science. Several ground-breaking events took place, in physics, biology and psychology. Planck introduced the quantum concept, the work of Mendel was rediscovered, and Sigmund Freud published The Interpretation of Dreams . These events heralded the emergence of completely new areas of inquiry, all of which greatly affected the intellectual landscape of the 20 th century, namely quantum physics, genetics and psychoanalysis. What do these developments have in common? Can we discern a family likeness, a (...) basic affinity between them, so that we can use the one to deepen our understanding of the other? One common denominator is that they open up realms of inquiry that are significantly different from the world of everyday experience, namely the realm of elementary particles, of genes and genomes, and of the unconscious. But to what extent can we meaningfully argue, for instance, that the genome is the biological unconscious, and the unconscious the psychic genome? To address these questions, I will build on the work of two key intellectual figures who have explored the affinities of these developments in depth, namely Erwin Schrödinger (a quantum physicist and avid reader of Schopenhauer who initiated molecular biology) and Jacques Lacan (who reframed the specificity of psychoanalysis with the help of 20 th century science: the era of structural linguistics, but also of quantum physics, molecular biology, bioinformatics and DNA). (shrink)

This volume celebrates the various facets of Alan Turing (1912–1954), the British mathematician and computing pioneer, widely considered as the father of computer science. It is aimed at the general reader, with additional notes and references for those who wish to explore the life and work of Turing more deeply. -/- The book is divided into eight parts, covering different aspects of Turing’s life and work. -/- Part I presents various biographical aspects of Turing, some from a personal point of (...) view. -/- Part II presents Turing’s universal machine (now known as a Turing machine), which provides a theoretical framework for reasoning about computation. His 1936 paper on this subject is widely seen as providing the starting point for the field of theoretical computer science. -/- Part III presents Turing’s working on codebreaking during World War II. While the War was a disastrous interlude for many, for Turing it provided a nationally important outlet for his creative genius. It is not an overstatement to say that without Turing, the War would probably have lasted longer, and may even have been lost by the Allies. The sensitive nature of Turning’s wartime work meant that much of this has been revealed only relatively recently. -/- Part IV presents Turing’s post-War work on computing, both at the National Physical Laboratory and at the University of Manchester. He made contributions to both hardware design, through the ACE computer at the NPL, and software, especially at Manchester. Part V covers Turing’s contribution to machine intelligence (now known as Artificial Intelligence or AI). Although Turing did not coin the term, he can be considered a founder of this field which is still active today, authoring a seminal paper in 1950. -/- Part VI covers morphogenesis, Turing’s last major scientific contribution, on the generation of seemingly random patterns in biology and on the mathematics behind such patterns. Interest in this area has increased rapidly in recent times in the field of bioinformatics, with Turing’s 1952 paper on this subject being frequently cited. -/- Part VII presents some of Turing’s mathematical influences and achievements. Turing was remarkably free of external influences, with few co-authors – Max Newman was an exception and acted as a mathematical mentor in both Cambridge and Manchester. -/- Part VIII considers Turing in a wider context, including his influence and legacy to science and in the public consciousness. -/- Reflecting Turing’s wide influence, the book includes contributions by authors from a wide variety of backgrounds. Contemporaries provide reminiscences, while there are perspectives by philosophers, mathematicians, computer scientists, historians of science, and museum curators. Some of the contributors gave presentations at Turing Centenary meetings in 2012 in Bletchley Park, King’s College Cambridge, and Oxford University, and several of the chapters in this volume are based on those presentations – some through transcription of the original talks, especially for Turing’s contemporaries, now aged in their 90s. Sadly, some contributors died before the publication of this book, hence its dedication to them. -/- For those interested in personal recollections, Chapters 2, 3, 11, 12, 16, 17, and 36 will be of interest. For philosophical aspects of Turing’s work, see Chapters 6, 7, 26–31, and 41. Mathematical perspectives can be found in Chapters 35 and 37–39. Historical perspectives can be found in Chapters 4, 8, 9, 10, 13–15, 18, 19, 21–25, 34, and 40. With respect to Turing’s body of work, the treatment in Parts II–VI is broadly chronological. We have attempted to be comprehensive with respect to all the important aspects of Turing’s achievements, and the book can be read cover to cover, or the chapters can be tackled individually if desired. There are cross-references between chapters where appropriate, and some chapters will inevitably overlap. -/- We hope that you enjoy this volume as part of your library and that you will dip into it whenever you wish to enter the multifaceted world of Alan Turing. (shrink)

Representing species-specific proteins and protein complexes in ontologies that are both human and machine-readable facilitates the retrieval, analysis, and interpretation of genome-scale data sets. Although existing protin-centric informatics resources provide the biomedical research community with well-curated compendia of protein sequence and structure, these resources lack formal ontological representations of the relationships among the proteins themselves. The Protein Ontology (PRO) Consortium is filling this informatics resource gap by developing ontological representations and relationships among proteins and their variants and modified forms. Because (...) proteins are often functional only as members of stable protein complexes, the PRO Consortium, in collaboration with existing protein and pathway databases, has launched a new initiative to implement logical and consistent representation of protein complexes. We describe here how the PRO Consortium is meeting the challenge of representing species-specific protein complexes, how protein complex representation in PRO supports annotation of protein complexes and comparative biology, and how PRO is being integrated into existing community bioinformatics resources. The PRO resource is accessible at http://pir.georgetown.edu/pro/. (shrink)

The 2013 Rostock Symposium on Systems Biology and Bioinformatics in Aging Research was again dedicated to dissecting the aging process using in silico means. A particular focus was on ontologies, as these are a key technology to systematically integrate heterogeneous information about the aging process. Related topics were databases and data integration. Other talks tackled modeling issues and applications, the latter including talks focussed on marker development and cellular stress as well as on diseases, in particular on diseases of (...) kidney and skin. (shrink)

Where humans can manipulate and integrate the information they receive in subtle and ever-changing ways from context to context, computers need structured and context-free background information of a sort which ontologies can help to provide. A domain ontology captures the stable, highly general and commonly accepted core knowledge for an application domain. The domain at issue here is that of the life sciences, in particular molecular biology and bioinformatics. Contemporary life science research includes components drawn from physics, chemistry, mathematics, (...) medicine and many other areas, and all of these dimensions, as well as fundamental philosophical issues, must be taken into account in the construction of a domain ontology. Here we describe the basic features of domain ontologies in the life sciences and show how they can be used. (shrink)

IntroductionBy ‘philosophy of consciousness’ we mean an assembly of different approaches such as philosophy of mind , perception, rational conclusions, information processing and contradictory conceptions such as holistic ‘all is mind’ perspectives and their atomistic counterparts.Since ancient Greeks philosophy has provided widespread debates on pneuma, nous, psyche, spiritus, mind, and Geist. In more recent times the philosophy of consciousness has become part of psychology, sociology, neuroscience, cognitive science, linguistics, communication science, information theory, cybernetic systems theory, synthetic biology, biolinguistics, bioinformatics (...) and biosemiotics.However, no matter what each of these approaches presents as a coherent explanation of the human mind, thinking, and consciousness, they remain alien to our self-awareness and self-reflection-based understanding because they do not offer a rational and at the same time .. (shrink)

Objective: microRNAs (miRNAs) have important potential as biomarkers in the diagnosis and prognosis of ischemia/reperfusion (I/R) injury in coronary artery bypass grafting surgery (CABG). This study investigated the relationship between preoperative (preop) and postoperative (post-op) cardiac parameters and miRNA expressions in CABG. -/- Methods: We analyzed a total of 94 individuals (CABG, n= 46 and healthy control, n=48). Quantitative real-time polymerase chain reaction (qRT) was performed to determine plasma miRNA expressions (miR-21, miR-181a, miR-199a, miR-199b, and miR-320a-5p) in triplicates: before surgery, (...) 1 hour after surgery, and 24 hours after surgery. The target genes and pathways of miRNA were determined using bioinformatic analysis. The biomarker potentials of miRNAs were evaluated with receiver operating characteristic (ROC) curve analysis. -/- Results: All miRNAs were significantly downregulated (p < 0.05). Troponin I, LVEF, CPK, and CK-MB were found to be statistically significant for operation groups (p < 0.05). miRNA expressions and cardiac markers were associated with troponin I and/or CK-MB. In ROC analyses, miR-199a was a good diagnostic marker. CREBRF and ZNF704 genes may be a target for these miRNAs. -/- Conclusions: Downregulation of miR-199a has a regulatory role in ischemia/reperfusion. They may contribute to CABG pathology through these two genes involved in signaling cascades to turn on protein response and ion binding. (shrink)

The Plant Ontology (PO; http://www.plantontology.org/) is a publicly-available, collaborative effort to develop and maintain a controlled, structured vocabulary (“ontology”) of terms to describe plant anatomy, morphology and the stages of plant development. The goals of the PO are to link (annotate) gene expression and phenotype data to plant structures and stages of plant development, using the data model adopted by the Gene Ontology. From its original design covering only rice, maize and Arabidopsis, the scope of the PO has been expanded (...) to include all green plants. The PO was the first multi-species anatomy ontology developed for the annotation of genes and phenotypes. Also, to our knowledge, it was one of the first biological ontologies that provides translations (via synonyms) in non-English languages such as Japanese and Spanish. There are about 2.2 million annotations linking PO terms to over 110,000 unique data objects representing genes or gene models, proteins, RNAs, germplasm and Quantitative Traits Loci (QTLs) from 22 plant species. In this paper, we focus on the plant anatomical entity branch of the PO, describing the organizing principles, resources available to users, and examples of how the PO is integrated into other plant genomics databases and web portals. We also provide two examples of comparative analyses, demonstrating how the ontology structure and PO-annotated data can be used to discover the patterns of expression of the LEAFY (LFY) and terpene synthase (TPS) gene homologs. (shrink)

The genomics “revolution” is spreading. Originating in the molecular life sciences, it initially affected a number of biomedical research fields such as cancer genomics and clinical genetics. Now, however, a new “wave” of genomic bioinformation is transforming a widening array of disciplines, including those that address the social, historical and cultural dimensions of human life. Increasingly, bioinformation is affecting “human sciences” such as psychiatry, psychology, brain research, behavioural research (“behavioural genomics”), but also anthropology and archaeology (“bioarchaeology”). Thus, bioinformatics is (...) having an impact on how we define and understand ourselves, how identities are formed and constituted, and, finally, on how we (on the basis of these redefined identities) assess and address some of the more concrete societal issues involved in genomics governance in various settings. This article explores how genomics and bioinformation, by influencing research agendas in the human sciences and the humanities, are affecting our self-image, our identity, the way we see ourselves. The impact of bioinformation on self-understanding will be assessed on three levels: (1) the collective level (the impact of comparative genomics on our understanding of human beings as a species), (2) the individual level (the impact of behavioural genomics on our understanding of ourselves as individuals), and (3) the genealogical level (the impact of population genomics on our understanding of human history, notably early human history). This threefold impact will be assessed from two seemingly incompatible philosophical perspectives, namely a “humanistic” perspective (represented in this article by Francis Fukuyama) and a “post-humanistic” one (represented by Peter Sloterdijk). On the basis of this analysis it will be concluded that, rather than focussing on human “enhancement” by adding or deleting genes, genome-oriented practices of the Self will focus on using genomics information in the context of identity-formation. Genomic bioinformation will increasingly be built into our self-images and used in order to tailor and adapt our practices of Self to our “personalised” genome. We will keep working on ourselves, no doubt, not by modifying our genomes, but rather by fine-tuning our behaviour. What we are experiencing is a bioinformatisation of the life-world. Genomics-based technologies will increasingly pervade our daily lives, our autobiographies and narratives, as well as our anthropologies, rather than our genomes as such. (shrink)

This text is an English translation of those several sections of the original paper in Russian, where collection-related issues are considered. The full citation of the original paper is as following: Pavlinov I.Ya. 2016. [Bioraznoobrazie i biokollektsii: problema sootvetstvia]. In: Pavlinov I.Ya. (comp.). Aspects of Biodiversity. Archives of Zoological Museum of Lomonosov Moscow State University, Vol. 54, Pр. 733–786. -/- Orientation of biology, as a natural science, on the study and explanation of the similarities and differences between organisms led in (...) the second half of the 20th century to the recognition of a specifi c subject area of biological explorations, viz. biodiversity (BD). One of the important general scientifi c prerequisites for this shift was understanding that (at the level of ontology) the structured diversity of the living nature is its fundamental property equivocal to subjecting of some of its manifestations to certain laws. At the level of epistemology, this led to acknowledging that the “diversifi cationary” approach to description of the living beings is as justifi able as the before dominated “unifi cationary” one. This general trend has led to a signifi cant increase in the attention to BD. From a pragmatic perspective, its leitmotif was conservation of BD as a renewable resource, while from a scientifi c perspective the leitmotif was studying it was studying BD as a specifi c natural phenomenon. These two points of view are united by recognition of the need for scientific substantiation of BD conservation strategy, which implies the need for a detailed study of BD itself. At the level of ontology, one of the key problems in the study of BD (leaving aside the question of its genesis) is determination of its structure, which is interpreted as a manifestation of the structure of the Earth’s biota itself. With this, it is acknowledged that the subject area of empirical explorations is not the BD as a whole ( “Umgebung”) but its particular manifestations (“Umwelts”). It is proposed herewith to recognized, within the latter: fragments of BD (especially taxa and ecosystems), hierarchical levels of BD (primarily within- and interorganismal ones), and aspects of BD (before all taxonomic and meronomic ones). Attention is drawn to a new interpretation of bioinformatics as a discipline that studies the information support of BD explorations. An important fraction of this support are biocollections. The scientifi c value of collections means that they make it possible both empirical inferring and testing (verification) of the knowledge about BD. This makes biocollections, in their epistemological status, equivalent to experiments, and so makes studies of BD quite scientific. It is emphasized that the natural objects (naturalia), which are permanently kept in collections, contain primary (objective) information about BD, while information retrieved somehow from them is a secondary (subjective) one. Collection, as an information resource, serves as a research sample in the studies of BD. Collection pool, as the totality of all collection materials kept in repositories according to certain standards, can be treated as a general sample, and every single collection as a local sample. The main characteristic of collection-as-sample is its representativeness; so the basic strategy of development of the collection pool is to maximize its representativeness as a means to ensure correspondence of structure of biocollection pool to that of BD itself. The most fundamental characteristic of collection, as an information resource, is its scientific signifi cance. The following three main groups of more particular characteristics are distinguished: — the “proper” characteristics of every collection are its meaningfulness, informativeness, reliability, adequacy, documenting, systematicity, volume, structure, uniqueness, stability, lability; — the “external” characteristics of collection are resolution, usability, ethic constituent; — the “service” characteristics of collection are its museofication, storage system security, inclusion in metastructure, cost. In the contemporary world, development of the biocollection pool, as a specific resource for BD research, requires considerable organizational efforts, including work on their “information support” aimed at demonstrating the necessity of existence of the biocollections. (shrink)

Dieses Buch betritt Neuland. Es ist eine Einführung in das neue Gebiet der angewandten Ontologie, jenem multidisziplinären Arbeitsgebiet, in dem Philosophen gemeinsam mit Informatikern und Vertretern der jeweils thematischen Wissenschaftsbereiche, in unserem Fall mit Biologen und Medizinern, daran arbeiten, wissenschaftliches Wissen informationstechnisch zu repräsentieren. Es zeigt, wie Philosophie eine praktische Anwendung findet, die von zunehmender Wichtigkeit nicht nur in den heutigen Lebenswissenschaften ist. Und so richtet sich dieses Buch an Philosophen, aber auch an interessierte Biologen, Mediziner und Informatiker.

Die bahnbrechenden wissenschaftlichen Ergebnisse der letzten Jahre erzwingen eine neue philosophische Auseinandersetzung mit den Grundkategorien der Biologie und der benachbarten Disziplinen. Insbesondere die Anwendung neuer informationstechnischer Mittel in der biomedizinischen Forschung und die damit verbundene, kontinuierlich zunehmende Datenflut sowie die Notwendigkeit, ihrer Herr zu werden, erfordern ein konsequentes Nachdenken darüber, wie biologische Daten systematisiert und klassifiziert werden können. Dafür wiederum bedarf es robuster Theorien von Grundbegriffen wie Art, Spezies, Teil, Ganzes, Funktion, Prozess, Fragment, Sequenz, Expression, Grenze, Locus, Umwelt, System usw. (...) Solche Begriffe gehören zum impliziten Wissen jedes Biologen. Sie spiegeln einerseits eine Dimension der biologischen Wirklichkeit wider, die auch vor dem Hintergrund der biologischen Evolution unverändert bleibt. Andererseits verlangt deren theoretische Behandlung nach zeitgemäßen Analoga der in der traditionellen aristotelischen Metaphysik entwickelten Methoden. Zugleich können so die explizit formulierten Theorien und Definitionen bereitgestellt werden, die für computergestützte Informationssysteme unabdingbar sind. Das Entwickeln derartiger Theorien und Definitionen ist eine Aufgabe der Philosophie, die in diesem Sinne herausgefordert ist, zwischen Biologie und Informatik zu vermitteln. (shrink)

The Salivaomics Knowledge Base (SKB) is designed to serve as a computational infrastructure that can permit global exploration and utilization of data and information relevant to salivaomics. SKB is created by aligning (1) the saliva biomarker discovery and validation resources at UCLA with (2) the ontology resources developed by the OBO (Open Biomedical Ontologies) Foundry, including a new Saliva Ontology (SALO). We define the Saliva Ontology (SALO; http://www.skb.ucla.edu/SALO/) as a consensus-based controlled vocabulary of terms and relations dedicated to the salivaomics (...) domain and to saliva-related diagnostics following the principles of the OBO (Open Biomedical Ontologies) Foundry. The Saliva Ontology is an ongoing exploratory initiative. The ontology will be used to facilitate salivaomics data retrieval and integration across multiple fields of research together with data analysis and data mining. The ontology will be tested through its ability to serve the annotation ('tagging') of a representative corpus of salivaomics research literature that is to be incorporated into the SKB. Background Saliva (oral fluid) is an emerging biofluid for non-invasive diagnostics used in the detection of human diseases. The need to advance saliva research is strongly emphasized by the National Institute of Dental and Craniofacial Research (NIDCR), and is included in the NIDCR's 2004- 2009 expert panel long-term research agenda [1]. The ability to monitor health status, disease onset, progression, recurrence and treatment outcome through noninvasive means is highly important to advancing health care management. Saliva is a perfect medium to be explored for personalized individual medicine including diagnostics, offering a non-invasive, easy to obtain means for detecting and monitoring diseases. Saliva testing potentially allows the patient to collect their own saliva samples at home, yielding convenience for the patient and savings in health costs, and facilitating multiple sampling. Specimen collection is less objectionable to patients and easier in children and elderly individuals. Due to these advantages. (shrink)

The Protein Ontology (PRO) is designed as a formal and principled Open Biomedical Ontologies (OBO) Foundry ontology for proteins. The components of PRO extend from a classification of proteins on the basis of evolutionary relationships at the homeomorphic level to the representation of the multiple protein forms of a gene, including those resulting from alternative splicing, cleavage and/or posttranslational modifications. Focusing specifically on the TGF-beta signaling proteins, we describe the building, curation, usage and dissemination of PRO. PRO provides a framework (...) for the formal representation of protein classes and protein forms in the OBO Foundry. It is designed to enable data retrieval and integration and machine reasoning at the molecular level of proteins, thereby facilitating cross-species comparisons, pathway analysis, disease modeling and the generation of new hypotheses. (shrink)

The Common Anatomy Reference Ontology (CARO) is being developed to facilitate interoperability between existing anatomy ontologies for different species, and will provide a template for building new anatomy ontologies. CARO has a structural axis of classification based on the top-level nodes of the Foundational Model of Anatomy. CARO will complement the developmental process sub-ontology of the GO Biological Process ontology, using it to ensure the coherent treatment of developmental stages, and to provide a common framework for the model organism communities (...) to classify developmental structures. Definitions for the types and relationships are being generated by a consortium of investigators from diverse backgrounds to ensure applicability to all organisms. CARO will support the coordination of cross-species ontologies at all levels of anatomical granularity by cross-referencing types within the cell type ontology (CL) and the Gene Ontology (GO) Cellular Component ontology. A complete cross-species CARO could be utilized in other ontologies for cross-product generation. (shrink)

Identification of non-coding RNAs (ncRNAs) has been significantly enhanced due to the rapid advancement in sequencing technologies. On the other hand, semantic annotation of ncRNA data lag behind their identification, and there is a great need to effectively integrate discovery from relevant communities. To this end, the Non-Coding RNA Ontology (NCRO) is being developed to provide a precisely defined ncRNA controlled vocabulary, which can fill a specific and highly needed niche in unification of ncRNA biology.

Research has indicated that microRNAs (miRNAs), a special class of non-coding RNAs (ncRNAs), can perform important roles in different biological and pathological processes. miRNAs’ functions are realized by regulating their respective target genes (targets). It is thus critical to identify and analyze miRNA-target interactions for a better understanding and delineation of miRNAs’ functions. However, conventional knowledge discovery and acquisition methods have many limitations. Fortunately, semantic technologies that are based on domain ontologies can render great assistance in this regard. In our (...) previous investigations, we developed a miRNA domain-specific application ontology, Ontology for MIcroRNA Target (OMIT), to provide the community with common data elements and data exchange standards in the miRNA research. This paper describes (1) our continuing efforts in the OMIT ontology development and (2) the application of the OMIT to enable a semantic approach for knowledge capture of miRNA-target interactions. (shrink)

Identification of non-coding RNAs (ncRNAs) has been significantly improved over the past decade. On the other hand, semantic annotation of ncRNA data is facing critical challenges due to the lack of a comprehensive ontology to serve as common data elements and data exchange standards in the field. We developed the Non-Coding RNA Ontology (NCRO) to handle this situation. By providing a formally defined ncRNA controlled vocabulary, the NCRO aims to fill a specific and highly needed niche in semantic annotation of (...) large amounts of ncRNA biological and clinical data. (shrink)

It is widely understood that protein functions can be exhaustively described in terms of no single parameter, whether this be amino acid sequence or the three-dimensional structure of the underlying protein molecule. This means that a number of different attributes must be used to create an ontology of protein functions. Certainly much of the required information is already stored in databases such as Swiss-Prot, Protein Data Bank, SCOP and MIPS. But the latter have been developed for different purposes and the (...) separate data-structures which they employ are not conducive to the needed data integration. When we attempt to classify the entities in the domain of proteins, we find ourselves faced with a number of cross-cutting principles of classification. Our question here is: how can we bring together these separate taxonomies in order to describe protein functions? Our proposed answer is: via a careful top-level ontological analysis of the relevant principles of classification, combined with a new framework for the simultaneous manipulation of classifications constructed for different purposes. (shrink)

that can serve as a foundation for more refined ontologies in the field of proteomics. Standard data sources classify proteins in terms of just one or two specific aspects. Thus SCOP (Structural Classification of Proteins) is described as classifying proteins on the basis of structural features; SWISSPROT annotates proteins on the basis of their structure and of parameters like post-translational modifications. Such data sources are connected to each other by pairwise term-to-term mappings. However, there are obstacles which stand in the (...) way of combining them together to form a robust meta-classification of the needed sort. We discuss some formal ontological principles which should be taken into account within the existing datasources in order to make such a metaclassification possible, taking into account also the Gene Ontology (GO) and its application to the annotation of proteins. (shrink)

The Cell Ontology (CL) is designed to provide a standardized representation of cell types for data annotation. Currently, the CL employs multiple is_a relations, defining cell types in terms of histological, functional, and lineage properties, and the majority of definitions are written with sufficient generality to hold across multiple species. This approach limits the CL’s utility for cross-species data integration. To address this problem, we developed a method for the ontological representation of cells and applied this method to develop a (...) dendritic cell ontology (DC-CL). DC-CL subtypes are delineated on the basis of surface protein expression, systematically including both species-general and species-specific types and optimizing DC-CL for the analysis of flow cytometry data. This approach brings benefits in the form of increased accuracy, support for reasoning, and interoperability with other ontology resources. 104. Barry Smith, “Toward a Realistic Science of Environments”, Ecological Psychology, 2009, 21 (2), April-June, 121-130. Abstract: The perceptual psychologist J. J. Gibson embraces a radically externalistic view of mind and action. We have, for Gibson, not a Cartesian mind or soul, with its interior theater of contents and the consequent problem of explaining how this mind or soul and its psychological environment can succeed in grasping physical objects external to itself. Rather, we have a perceiving, acting organism, whose perceptions and actions are always already tuned to the parts and moments, the things and surfaces, of its external environment. We describe how on this basis Gibson sought to develop a realist science of environments which will be ‘consistent with physics, mechanics, optics, acoustics, and chemistry’. (shrink)

It is now increasingly accepted that many existing biological and medical ontologies can be improved by adopting tools and methods that bring a greater degree of logical and ontological rigor. In this chapter we will focus on the merits of a logically sound approach to ontologies from a methodological point of view. As we shall see, one crucial feature of a logically sound approach is that we have clear and functional definitions of the relational expressions such as ‘is a’ and (...) ‘part of ’. (shrink)

I'll show that the kind of analogy between life and information [argued for by authors such as Davies (2000), Walker and Davies (2013), Dyson (1979), Gleick (2011), Kurzweil (2012), Ward (2009)] – that seems to be central to the effect that artificial mind may represent an expected advance in the life evolution in the Universe – is like the design argument, and that if the design argument is unfounded and invalid, the argument to the effect that artificial mind may represent (...) an expected advance in the life evolution in the Universe is also unfounded and invalid. However, if we are prepared to admit (though we should not do so) this method of reasoning as valid, I'll show that the analogy between life and information to the effect that artificial mind may represent an expected advance in the evolution of life in the Universe seems to suggest some type of reductionism of life to information, but biology respectively chemistry, or physics are not reductionist, contrary to what seems to be suggested by the analogy between life and information. (shrink)

In the first section, Introduction, we present our experimental design. In the second section, we characterise the grand average occipital and temporal electrical activity correlated with a contrast in access. In the third section, we characterise the grand average occipital and temporal electrical activity correlated with a contrast in phenomenology and conclude characterising the grand average occipital and temporal electrical activity co-occurring with unconsciousness.

A wide variety of ontologies relevant to the biological and medical domains are available through the OBO Foundry portal, and their number is growing rapidly. Integration of these ontologies, while requiring considerable effort, is extremely desirable. However, heterogeneities in format and style pose serious obstacles to such integration. In particular, inconsistencies in naming conventions can impair the readability and navigability of ontology class hierarchies, and hinder their alignment and integration. While other sources of diversity are tremendously complex and challenging, agreeing (...) a set of common naming conventions is an achievable goal, particularly if those conventions are based on lessons drawn from pooled practical experience and surveys of community opinion. We summarize a review of existing naming conventions and highlight certain disadvantages with respect to general applicability in the biological domain. We also present the results of a survey carried out to establish which naming conventions are currently employed by OBO Foundry ontologies and to determine what their special requirements regarding the naming of entities might be. Lastly, we propose an initial set of typographic, syntactic and semantic conventions for labelling classes in OBO Foundry ontologies. Adherence to common naming conventions is more than just a matter of aesthetics. Such conventions provide guidance to ontology creators, help developers avoid flaws and inaccuracies when editing, and especially when interlinking, ontologies. Common naming conventions will also assist consumers of ontologies to more readily understand what meanings were intended by the authors of ontologies used in annotating bodies of data. (shrink)

Many existing biomedical vocabulary standards rest on incomplete, inconsistent or confused accounts of basic terms pertaining to diseases, diagnoses, and clinical phenotypes. Here we outline what we believe to be a logically and biologically coherent framework for the representation of such entities and of the relations between them. We defend a view of disease as involving in every case some physical basis within the organism that bears a disposition toward the execution of pathological processes. We present our view in the (...) form of a list of terms and definitions designed to provide a consistent starting point for the representation of both disease and diagnosis in information systems in the future. (shrink)

Biomedical ontologies are emerging as critical tools in genomic and proteomic research where complex data in disparate resources need to be integrated. A number of ontologies exist that describe the properties that can be attributed to proteins; for example, protein functions are described by Gene Ontology, while human diseases are described by Disease Ontology. There is, however, a gap in the current set of ontologies—one that describes the protein entities themselves and their relationships. We have designed a PRotein Ontology (PRO) (...) to facilitate protein annotation and to guide new experiments. The components of PRO extend from the classification of proteins on the basis of evolutionary relationships to the representation of the multiple protein forms of a gene (products generated by genetic variation, alternative splicing, proteolytic cleavage, and other post-translational modification). PRO will allow the specification of relationships between PRO, GO and other OBO Foundry ontologies. Here we describe the initial development of PRO, illustrated using human proteins from the TGF-beta signaling pathway. (shrink)

Formal principles governing best practices in classification and definition have for too long been neglected in the construction of biomedical ontologies, in ways which have important negative consequences for data integration and ontology alignment. We argue that the use of such principles in ontology construction can serve as a valuable tool in error-detection and also in supporting reliable manual curation. We argue also that such principles are a prerequisite for the successful application of advanced data integration techniques such as ontology-based (...) multi-database querying, automated ontology alignment and ontology-based text-mining. These theses are illustrated by means of a case study of the Gene Ontology, a project of increasing importance within the field of biomedical data integration. (shrink)

Successful biomedical data mining and information extraction require a complete picture of biological phenomena such as genes, biological processes, and diseases; as these exist on different levels of granularity. To realize this goal, several freely available heterogeneous databases as well as proprietary structured datasets have to be integrated into a single global customizable scheme. We will present a tool to integrate different biological data sources by mapping them to a proprietary biomedical ontology that has been developed for the purposes of (...) making computers understand medical natural language. (shrink)