The Protein Ontology (PRO) provides a formal, logically-based classification of specific protein classes including structured representations of protein isoforms, variants and modified forms. Initially focused on proteins found in human, mouse and Escherichia coli, PRO now includes representations of protein complexes. The PRO Consortium works in concert with the developers of other biomedical ontologies and protein knowledge bases to provide the ability to formally organize and integrate representations of precise protein forms so as (...) to enhance accessibility to results of protein research. PRO (http://pir.georgetown.edu/pro) is part of the Open Biomedical Ontologies (OBO) Foundry. (shrink)

The Protein Ontology (PRO; http://proconsortium.org) formally defines protein entities and explicitly represents their major forms and interrelations. Protein entities represented in PRO corresponding to single amino acid chains are categorized by level of specificity into family, gene, sequence and modification metaclasses, and there is a separate metaclass for protein complexes. All metaclasses also have organism-specific derivatives. PRO complements established sequence databases such as UniProtKB, and interoperates with other biomedical and biological ontologies such as the Gene (...) Ontology (GO). PRO relates to UniProtKB in that PRO’s organism-specific classes of proteins encoded by a specific gene correspond to entities documented in UniProtKB entries. PRO relates to the GO in that PRO’s representations of organism-specific protein complexes are subclasses of the organism-agnostic protein complex terms in the GO Cellular Component Ontology. The past few years have seen growth and changes to the PRO, as well as new points of access to the data and new applications of PRO in immunology and proteomics. Here we describe some of these developments. (shrink)

The Protein Ontology (PRO) web resource provides an integrative framework for protein-centric exploration and enables specific and precise annotation of proteins and protein complexes based on PRO. Functionalities include: browsing, searching and retrieving, terms, displaying selected terms in OBO or OWL format, and supporting URIs. In addition, the PRO website offers multiple ways for the user to request, submit, or modify terms and/or annotation. We will demonstrate the use of these tools for protein research and (...) annotation. (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)

The Protein Ontology provides terms for and supports annotation of species-specific protein complexes in an ontology framework that relates them both to their components and to species-independent families of complexes. Comprehensive curation of experimentally known forms and annotations thereof is expected to expose discrepancies, differences, and gaps in our knowledge. We have annotated the early events of innate immune signaling mediated by Toll-Like Receptor 3 and 4 complexes in human, mouse, and chicken. The resulting ontology (...) and annotation data set has allowed us to identify species-specific gaps in experimental data and possible functional differences between species, and to employ inferred structural and functional relationships to suggest plausible resolutions of these discrepancies and gaps. (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)

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)

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)

The protein folding problem is one of the foundational problems of biochemistry and it is still considered unsolved. It basically consists of two main questions: what are the factors determining the stability of the protein’s native structure and how does the protein acquire it starting from an unfolded state. Since its first formulation, two main explanatory approaches have dominated the field of protein folding research: a thermodynamic approach focused on energetic features and a kinetic approach focused (...) on the temporal development of protein chains and structural considerations. Although these two approaches are tightly intertwined in biochemical practice and largely agree on which are the parts and activities in which the phenomenon under study should be decomposed to, there nevertheless exist important contrasts that have had repercussions on the development of the field and still engender vigorous debate. We shall analyse the historical development of the field and crucial aspects of current scientific debates. On this basis, we argue that the main sources of disagreement centre on the causal interpretation of thermodynamic and kinetic explanations, on the explanatory relevance assigned to different features of the phenomena under study and on the status of the ontological assumptions concerning the entities under study. (shrink)

We have begun work on two separate but related ontologies for the study of neurological diseases. The first, the Neurological Disease Ontology (ND), is intended to provide a set of controlled, logically connected classes to describe the range of neurological diseases and their associated signs and symptoms, assessments, diagnoses, and interventions that are encountered in the course of clinical practice. ND is built as an extension of the Ontology for General Medical Sciences — a high-level candidate OBO Foundry (...) ontology that provides a set of general classes that can be used to describe general aspects of medical science. ND is being built with classes utilizing both textual and axiomatized definitions that describe and formalize the relations between instances of other classes within the ontology itself as well as to external ontologies such as the Gene Ontology, Cell Ontology, Protein Ontology, and Chemical Entities of Biological Interest. In addition, references to similar or associated terms in external ontologies, vocabularies and terminologies are included when possible. Initial work on ND is focused on the areas of Alzheimer’s and other diseases associated with dementia, multiple sclerosis, and stroke and cerebrovascular disease. Extensions to additional groups of neurological diseases are planned. The second ontology, the Neuro-Psychological Testing Ontology (NPT), is intended to provide a set of classes for the annotation of neuropsychological testing data. The intention of this ontology is to allow for the integration of results from a variety of neuropsychological tests that assay similar measures of cognitive functioning. Neuro-psychological testing is an important component in developing the clinical picture used in the diagnosis of patients with a range of neurological diseases, such as Alzheimer’s disease and multiple sclerosis, and following stroke or traumatic brain injury. NPT is being developed as an extension to the Ontology for Biomedical Investigations. (shrink)

Biochemical kinds such as proteins pose interesting problems for philosophers of science, as they can be studied from the points of view of both biology and chemistry. The relationship between the biological functions of biochemical kinds and the microstructures that they are related to is the key question. This leads us to a more general discussion about ontological reductionism, microstructuralism, and multiple realization at the biology-chemistry interface. On the face of it, biochemical kinds seem to pose a challenge for ontological (...) reductionism and hence motivate a dual theory of chemical and biological kinds, a type of pluralism about natural kinds. But it will be argued that the challenge, which is based on multiple realization, can be addressed. The upshot is that there are reasonable prospects for ontological reductionism about biochemical kinds, which corroborates natural kind monism. (shrink)

A longstanding philosophical premise perceives simplicity as a desirable attribute of scientific theories. One of several raised justifications for this notion is that simple theories are more likely to indicate the true makeup of natural systems. Qualitatively parsimonious hypotheses and theories keep to a minimum the number of different postulated entities within a system. Formulation of such ontologically simple working hypotheses proved to be useful in the experimental probing of narrowly defined bio systems. It is less certain, however, whether qualitatively (...) parsimonious theories are effective indicators of the true nature of complex biological systems. This paper assesses the success of ontologically simple theories in envisaging the makeup of three complex systems in bacteriology, immunology, and molecular biology. Evidence shows that parsimonious theories completely misconstrued the actual ontologically complex constitutions of the three examined systems. Since evolution and selective pressures typically produce ontologically intricate rather than simple bio systems, qualitatively parsimonious theories are mostly inapt indicators of the true nature of complex biological systems. (shrink)

Vaccine research, as well as the development, testing, clinical trials, and commercial uses of vaccines involve complex processes with various biological data that include gene and protein expression, analysis of molecular and cellular interactions, study of tissue and whole body responses, and extensive epidemiological modeling. Although many data resources are available to meet different aspects of vaccine needs, it remains a challenge how we are to standardize vaccine annotation, integrate data about varied vaccine types and resources, and support advanced (...) vaccine data analysis and inference. To address these problems, the community-based Vaccine Ontology (VO) has been developed through collaboration with vaccine researchers and many national and international centers and programs, including the National Center for Biomedical Ontology (NCBO), the Infectious Disease Ontology (IDO) Initiative, and the Ontology for Biomedical Investigations (OBI). VO utilizes the Basic Formal Ontology (BFO) as the top ontology and the Relation Ontology (RO) for definition of term relationships. VO is represented in the Web Ontology Language (OWL) and edited using the Protégé-OWL. Currently VO contains more than 2000 terms and relationships. VO emphasizes on classification of vaccines and vaccine components, vaccine quality and phenotypes, and host immune response to vaccines. These reflect different aspects of vaccine composition and biology and can thus be used to model individual vaccines. More than 200 licensed vaccines and many vaccine candidates in research or clinical trials have been modeled in VO. VO is being used for vaccine literature mining through collaboration with the National Center for Integrative Biomedical Informatics (NCIBI). Multiple VO applications will be presented. (shrink)

One of the foundational problems of biochemistry concerns the conceptualisation of the relationship between the composition, structure and function of macromolecules like proteins. Part of the recent philosophical literature displays a reductionist bias, that is, the endorsement of a form of microstructuralism mirroring an out-dated biochemical conceptualisation. We shall argue that such microstructuralist approaches are ultimately committed to a potentialist form of micro-predeterminism whereby the macrostructure and function of proteins is accounted for solely in terms of the intrinsic properties and (...) potentialities of the components of the primary structure as if they were self-contained or essentially immutable entities. We shall instead suggest that a conceptualisation of the relationship between proteins’ composition, structure and function consistent with contemporary biochemical practice should account also for the causal role of the cellular, organismal and environmental relations in protein development. The analysis of the folding process we propose suggests that microstructure-laden reductionist approaches are ontologically indefensible. Rather than a potentialist form of micro-predeterminism, our analysis ultimately supports a relational-construction-based view of protein development and potentialities formation, which requires an indispensable analysis of the dynamical interplay between the micro-level of the parts and the macro-level of the relational structures of their systems. (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)

How and why, historian of science Lily Kay asks, did the ‘biological problem of DNA-based protein synthesis’ come to be represented ‘as an information code and a writing technology?’ What sort of metaphor was ‘code’ for these bio-geneticists? One whose run-away expansion, Derrida noted in Of Grammatology (1967), urgently required philosophical justification. Yet, 60 years later, there is still fundamental disagreement about its meaning and epistemic status. If the metaphor lacks ontological purchase, what accounts for its effectiveness? If, on (...) the other hand, scriptural metaphors get at the common root of culture and biology, what do we now mean by ‘code’? In this article, I trace several influential accounts of the metaphor’s effectiveness—making explicit the opposing notions of ‘code’ that animate them—and argue that each is too limited. Greater attention to the metaphoricity of ‘code’ yields a more philosophically productive and critical account of the metaphor of code. (shrink)

The automatic integration of rapidly expanding information resources in the life sciences is one of the most challenging goals facing biomedical research today. Controlled vocabularies, terminologies, and coding systems play an important role in realizing this goal, by making it possible to draw together information from heterogeneous sources – for example pertaining to genes and proteins, drugs and diseases – secure in the knowledge that the same terms will also represent the same entities on all occasions of use. In the (...) naming of genes, proteins, and other molecular structures, considerable efforts are under way to reduce the effects of the different naming conventions which have been spawned by different groups of researchers. Electronic patient records, too, increasingly involve the use of standardized terminologies, and tremendous efforts are currently being devoted to the creation of terminology resources that can meet the needs of a future era of personalized medicine, in which genomic and clinical data can be aligned in such a way that the corresponding information systems become interoperable. (shrink)

According to process ontology in the philosophy of biology, the living world is better understood as processes rather than as substantial individuals. Within this perspective, an organism does not consist of a hierarchy of structures like a machine, but rather a dynamic hierarchy of processes, dynamically maintained and stabilized at different time scales. With this respect, two processual approaches on enzymes by Stein (Hyle Int J Philos Chem 10(4):5–22, 2004, Process Stud 34:62–80, 2005, Found Chem 8:3–29, 2006) and by (...) Guttinger (Everything Flows: Towards a Processual Philosophy of Biology, Oxford University Press, Oxford, 2018) allows to think of macromolecules as relational and processual entities. In this work, I propose to extend their arguments to another case study within the biochemical domain, which is the case of ligand receptors and receptor-mediated biosignaling. The aim of this work is to analyze the case of G Protein-Coupled Receptors and biosignaling under the consideration of a processual ontology. I will defend that the processual ontology framework is adequate for the biochemical domain and that it allows accounting for the current biochemical knowledge related to the case study. (shrink)

According to process ontology in the philosophy of biology, the living world is better understood as processes rather than as substantial individuals. Within this perspective, an organism does not consist of a hierarchy of structures like a machine, but rather a dynamic hierarchy of processes, dynamically maintained and stabilized at different time scales. With this respect, two processual approaches on enzymes by Stein (Hyle Int J Philos Chem 10(4):5–22, 2004, Process Stud 34:62–80, 2005, Found Chem 8:3–29, 2006) and by (...) Guttinger (Everything Flows: Towards a Processual Philosophy of Biology, Oxford University Press, Oxford, 2018) allows to think of macromolecules as relational and processual entities. In this work, I propose to extend their arguments to another case study within the biochemical domain, which is the case of ligand receptors and receptor-mediated biosignaling. The aim of this work is to analyze the case of G Protein-Coupled Receptors and biosignaling under the consideration of a processual ontology. I will defend that the processual ontology framework is adequate for the biochemical domain and that it allows accounting for the current biochemical knowledge related to the case study. (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)

Mitchell & Gronenborn ( 2017 ) propose that we account for the presence of multiple models of protein structure, each produced in different contexts, through the framework of integrative pluralism. I argue that two interpretations of this framework are available, neither of which captures the relationship between a model and the protein structure it represents or between multiple models of protein structure. Further, it inclines us toward concluding prematurely that models of protein structure are right in (...) their contexts and makes extrapolation of findings from one context to another seem unwarranted. Instead, protein structure determination ought to be understood as _modestly monistic_. There is one model for every protein in each physicochemical context, and models of the same protein produced in different contexts are compatible with one another. ‘Integrating’ multiple models amounts to extrapolating from one context to another; this is possible because the effect of context on protein folding is relatively weak and predictable. Modest monism better describes the practice of protein structure determination than integrative pluralism and enables greater attention to how context affects protein folding. (shrink)

In this article, I draw on my fieldwork creating protein models of hepatitis B at a biotech laboratory to think through how to approach the body and disease from ontological and phenomenological perspectives. I subsequently draw on Mariella Pandolfi’s work on how bodies can be made to suffer history and Paul Farmer’s work on global tuberculosis disparities to explore ways of analysing embodied activity as a means of identifying and clinically addressing enactments of social inequality and disease. I also (...) introduce Merleau-Ponty’s phenomenological concept of ‘flesh’ as a conceptual heuristic that allows us to understand the meaningful structuring of ontological worlds beyond our own. As I argue, bringing these perspectives together not only allows us to re-envision what an effective disease treatment should be in diverse medical contexts, but also how to better understand health disparities and the nature of disease itself. (shrink)

Ontologies are being developed throughout the biomedical sciences to address standardization, integration, classification and reasoning needs against the background of an increasingly data-driven research paradigm. In particular, ontologies facilitate the translation of basic research into benefits for the patient by making research results more discoverable and by facilitating knowledge transfer across disciplinary boundaries. Addressing and adequately treating mental illness is one of our most pressing public health challenges. Primary research across multiple disciplines such as psychology, psychiatry, biology, neuroscience and pharmacology (...) needs to be integrated in order to promote a more comprehensive understanding of underlying processes and mechanisms, and this need for integration only becomes more pressing with our increase in understanding of differences among individuals and populations at the molecular level concerning susceptibility to specific illnesses. Substance addiction is a particularly relevant public health challenge in the developed world, affecting a substantial percentage of the population, often co-morbid with other illnesses such as mood disorders. Currently, however, there is no straightforward automated method to combine data of relevance to the study of substance addiction across multiple disciplines and populations. In this contribution, we describe a framework of interlinked, interoperable bio-ontologies for the annotation of primary research data relating to substance addiction, and discuss how this framework enables easy integration of results across disciplinary boundaries. We describe entities and relationships relevant for the description of addiction within the Mental Functioning Ontology, Chemical Entities of Biological Interest Ontology, Protein Ontology, Gene Ontology and the Neuroscience Information Framework ontologies. (shrink)

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the (...) development of the community-based Coronavirus Infectious Disease Ontology in early 2020. -/- As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. -/- CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications. (shrink)

Systems biology has provided new resources for discovering and reasoning about mechanisms. In addition to generating databases of large bodies of data, systems biologists have introduced platforms such as Cytoscape to represent protein–protein interactions, gene interactions, and other data in networks. Networks are inherently flat structures. One can identify clusters of highly connected nodes, but network representations do not represent these clusters as at a higher level than their constituents. Mechanisms, however, are hierarchically organized: they can be decomposed (...) into their parts and their activities can be decomposed into component operations. A potent bridge between flat networks and hierarchical mechanisms is provided by biological ontologies, both those curated by hand such as Gene Ontology and those extracted directly from databases such as Network Extracted Ontology. I examine several examples in which by applying ontologies to networks, systems biologists generate new hypotheses about mechanisms and characterize these novel strategies for developing mechanistic explanations. (shrink)

The Cell Cycle Ontology (CCO) has the aim to provide a 'one stop shop' for scientists interested in the biology of the cell cycle that would like to ask questions from a molecular and/or systems perspective: what are the genes, proteins, and so on involved in the regulation of cell division? How do they interact to produce the effects observed in the regulation of the cell cycle? To answer these questions, the CCO must integrate a large amount of knowledge (...) from diverse sources; the irregularity and incompleteness of this information suggests an ontology can act as the means of this integration. The volatility and continued expansion of biological knowledge means the content and modelling of the CCO will have to be frequently changed and updated. The CCO is generated from the input data automatically once every two months. This makes it easy to change the representation to enable certain queries; incorporate new knowledge; and consistently apply design patterns across the CCO. The automatic process also allows the CCO to be delivered in a variety of representations that suit the needs of various CCO customers and the abilities of existing toolsets. In this paper we present the CCO and its characteristics of utility and flexibility, that, from our perspective, make it a beautiful ontology. (shrink)

The viability of enactivist philosophy in providing descriptions of biological phenomena across the phylogenetic spectrum relies in large part on the scalability of its central concepts, i.e. whether they remain operative at varying levels of biological complexity. In this paper, I will examine the possibility of scaling two deeply intertwined concepts: cognition and surrounding world. Contra some indications from Varela and others, I will argue that the concept of embodied cognition can be scaled down below the level of the organism. (...) I will draw upon the “cognitive biology” espoused by Kováč and Monod’s studies of protein behaviour to make this case. The downscaling of embodied cognition below the level of the organism has ramifications for how we understand the concept of surrounding world. Reconfiguring the relation between these two central bioenactive concepts has further consequences for what ontological commitments bioenactive thinking leads to, and what paths of investigation it points us toward. (shrink)

A review of U. Mäki (ed.). Fact and Fiction in Economics, Cambridge: Cambridge University Press, 2003. pp. xvi 384. ISBN 0521 00957. As people interested mainly in theory, methodologists and philos...

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 paper begins with a more carefully stated version of ontologically neutral (ON) logic, originally introduced in (Hailperin, 1997). A non-infinitistic semantics which includes a definition of potential infinite validity follows. It is shown, without appeal to the actual infinite, that this notion provides a necessary and sufficient condition for provability in ON logic.

While Darwin is commonly supposed to have demonstrated the inapplicability of the Aristotelian ontology of species to biological science, recent developments, especially in the wake of the Human Genome Project, have given rise to a new golden age of classification in which ontological ideas -- as for example in the Gene Ontology, the Cell Ontology, the Protein Ontology, and so forth -- are once again playing an important role. In regard to species, on the other (...) hand, matters are more complex. We provide a brief overview of recent proposals concerning the ontology of species, dealing with species as sets, classes and as collections, the views of Ernst Meyr, and mereological views. (shrink)