This paper is concerned with reasonings that purport to explain why certain organisms have certain traits by showing that their actual design is better than contrasting designs. Biologists call such reasonings 'functional explanations'. To avoid confusion with other uses of that phrase, I call them 'design explanations'. This paper discusses the structure of design explanations and how they contribute to scientific understanding. Design explanations are contrastive and often compare real organisms to hypothetical organisms that cannot possibly exist. They are not (...) causal but appeal to functional dependencies between an organism's different traits. These explanations point out that because an organism has certain traits, it cannot be alive if the trait to be explained were replaced by a specified alternative. They can be understood from a mechanistic point of view as revealing the constraints on what mechanisms can be alive. (shrink)

Model organismism—the over-reliance on model organisms without sufficient attention to the adequacy of the models—continues to hobble our understanding of human brains and behaviors. I outline the problem of model organismism in contemporary biology and biomedicine, and discuss the virtues of a genuinely comparative biology for understanding ourselves, our evolutionary history, and our place in nature.

It is one of the central aims of the philosophy of science to elucidate the meanings of scientific terms and also to think critically about their application. The focus of this essay is the scientific term predict and whether there is credible evidence that animal models, especially in toxicology and pathophysiology, can be used to predict human outcomes. Whether animals can be used to predict human response to drugs and other chemicals is apparently a contentious issue. However, when one empirically (...) analyzes animal models using scientific tools they fall far short of being able to predict human responses. This is not surprising considering what we have learned from fields such evolutionary and developmental biology, gene regulation and expression, epigenetics, complexity theory, and comparative genomics. (shrink)

This paper aims to clarify the consequences of new scientific and philosophical approaches for the practical-theoretical framework of modern developmental biology. I highlight normal development, and the instructive-permissive distinction, as key parts of this framework which shape how variation is conceptualised and managed. Furthermore, I establish the different dimensions of biological variation: the units, temporality and mode of variation. Using the analytical frame established by this, I interpret a selection of examples as challenges to the instructive-permissive distinction. These examples include (...) the phenomena of developmental plasticity and transdifferentiation, the role of the microbiome in development, and new methodological approaches to standardisation and the assessment of causes. Furthermore, I argue that investigations into organismal development should investigate the effects of a wider range of kinds of variation including variation in the units, modes and temporalities of development. I close by examining various possible opportunities for producing and using normal development free of the assumptions of the instructive-permissive distinction. These opportunities are afforded by recent developments, which include new ways of producing standards incorporating more natural variation and being based on function rather than structure, and the ability to produce, store, and process large quantities of data. (shrink)

After 1900, the selective breeding of a few standard animals for research in the life sciences changed the way science was done. Among the pervasive changes was a transformation in scientists' assumptions about relationship between diversity and generality. Examination of the contents of two prominent physiology journals between 1885 and 1900, reveals that scientists used a diverse array of organisms in empirical research. Experimental physiologists gave many reasons for the choice of test animals, some practical and others truly comparative. But, (...) despite strong philosophical differences in the approaches they represented, the view that it was best to incorporate as many species as possible into research on physiological processes was widespread in both periodicals. Authors aimed for generality, but they treated it as a conclusion that would or would not follow from the examination of many species. After 1900, an increasing emphasis on standardization, the growth of the experimental method and the growing industrialization of the life sciences led to a decline in the number of species used in research. In this context, the selective breeding of animals for science facilitated a change in assumptions about the relationship between generality and diversity. As animals were increasingly viewed as things that were assumed to be fundamentally similar, scientific generality became an a priori assumption rather than an empirical conclusion. (shrink)

Community databases have become crucial to the collection, ordering and retrieval of data gathered on model organisms, as well as to the ways in which these data are interpreted and used across a range of research contexts. This paper analyses the impact of community databases on research practices in model organism biology by focusing on the history and current use of four community databases: FlyBase, Mouse Genome Informatics, WormBase and The Arabidopsis Information Resource. We discuss the standards used by the (...) curators of these databases for what counts as reliable evidence, acceptable terminology, appropriate experimental set-ups and adequate materials (e.g., specimens). On the one hand, these choices are informed by the collaborative research ethos characterising most model organism communities. On the other hand, the deployment of these standards in databases reinforces this ethos and gives it concrete and precise instantiations by shaping the skills, practices, values and background knowledge required of the database users. We conclude that the increasing reliance on community databases as vehicles to circulate data is having a major impact on how researchers conduct and communicate their research, which affects how they understand the biology of model organisms and its relation to the biology of other species. (shrink)

Life scientists increasingly rely upon abstraction-based modeling and reasoning strategies for understanding biological phenomena. We introduce the notion of constraint-based reasoning as a fruitful tool for conceptualizing some of these developments. One important role of mathematical abstractions is to impose formal constraints on a search space for possible hypotheses and thereby guide the search for plausible causal models. Formal constraints are, however, not only tools for biological explanations but can be explanatory by virtue of clarifying general dependency-relations and patterning between (...) functions and structures. We describe such situations as constraint-based explanations and argue that these differ from mechanistic strategies in important respects. While mechanistic explanations emphasize change-relating causal features, constraint-based explanations emphasize formal dependencies and generic organizational features that are relatively independent of lower-level changes in causal details. Our distinction between mechanistic and constraint-based explanations is pragmatically motivated by the wish to understand scientific practice. We contend that delineating the affordances and assumptions of different explanatory questions and strategies helps to clarify tensions between diverging scientific practices and the innovative potentials in their combination. Moreover, we show how constraint-based explanation integrates several features shared by otherwise different philosophical accounts of abstract explanatory strategies in biology. (shrink)

This paper aims to identify the key characteristics of model organisms that make them a specific type of model within the contemporary life sciences: in particular, we argue that the term “model organism” does not apply to all organisms used for the purposes of experimental research. We explore the differences between experimental and model organisms in terms of their material and epistemic features, and argue that it is essential to distinguish between their representational scope and representational target. We also examine (...) the characteristics of the communities who use these two types of models, including their research goals, disciplinary affiliations, and preferred practices to show how these have contributed to the conceptualization of a model organism. We conclude that model organisms are a specific subgroup of organisms that have been standardized to fit an integrative and comparative mode of research, and that it must be clearly distinguished from the broader class of experimental organisms. In addition, we argue that model organisms are the key components of a unique and distinctively biological way of doing research using models.Keywords: Experimental organism; Genetics; Model organism; Modeling; Philosophy of biology; Representation. (shrink)

ArgumentWe examine the criteria used to validate the use of nonhuman organisms in North-American alcohol addiction research from the 1950s to the present day. We argue that this field, where the similarities between behaviors in humans and non-humans are particularly difficult to assess, has addressed questions of model validity by transforming the situatedness of non-human organisms into an experimental tool. We demonstrate that model validity does not hinge on the standardization of one type of organism in isolation, as often the (...) case with genetic model organisms. Rather, organisms are viewed as necessarily situated: they cannot be understood as a model for human behavior in isolation from their environmental conditions. Hence the environment itself is standardized as part of the modeling process; and model validity is assessed with reference to the environmental conditions under which organisms are studied. (shrink)

The basic principles of scientific research from the great French physiologist whose contributions in the 19th century included the discovery of vasomotor nerves; nature of curare and other poisons in human body; more.

This book offers a philosophy for error-prone humans trying to understand messy systems in the real world.

Idealization is a reasoning strategy that biologists use to describe, model and explain that purposefully departs from features known to be present in nature. Similar to other strategies of scientific reasoning, idealization combines distinctive strengths alongside of latent weaknesses. The study of ontogeny in model organisms is usually executed by establishing a set of normal stages for embryonic development, which enables researchers in different laboratory contexts to have standardized comparisons of experimental results. Normal stages are a form of idealization because (...) they intentionally ignore known variation in development, including variation associated with phenotypic plasticity (e.g. via strict control of environmental variables). This is a tension between the phenomenon of plasticity and the practice of staging that has consequences for evolutionary developmental investigation because variation is conceptually removed as a part of rendering model organisms experimentally tractable. Two compensatory tactics for mitigating these consequences are discussed: employing a diversity of model organisms and adopting alternative periodizations. (shrink)