Ethology brought some crucial insights and perspectives to the study of behavior, in particular the idea that behavior can be studied within a comparative-evolutionary framework by means of homologizing components of behavioral patterns and by causal analysis of behavior components and their integration. Early ethology is well-known for its extensive use of qualitative observations of animals under their natural conditions. These observations are combined with experiments that try to analyze behavioral patterns and establish specific claims about animal behavior. Nowadays, there (...) is still disagreement about the significance of observation and experiments and their relation. (shrink)

Among recent developments in the anthropological sciences, hardly any have found so much attention and led to so much controversy as have the views advanced by the late Benjamin Whorf.The hypothesis offered by Whorf is,“that the commonly held belief that the cognitive processes of all human beings possess a common logical structure which operates prior to and independently of communication through language, is erroneous. It is Whorf's view that the linguistic patterns themselves determine what the individual perceives in this world (...) and how he thinks about it. Since these patterns vary widely, the modes of thinking and perceiving in groups utilizing different linguistic systems will result in basically different world views”.“We are thus introduced to a new principle of relativity which holds that all observers are not led by the same physical evidence to the same picture of the universe, unless their linguistic backgrounds are similar. … We cut up and organize the spread and flow of events as we do largely because, through our mother tongue, we are parties to an agreement to do so, not because nature itself is segmented in exactly that way for all to see”. (shrink)

There are many things that philosophy of biology might be. But, given the existence of a professional philosophy of biology that is arguably a progressive research program and, as such, unrivaled, it makes sense to define philosophy of biology more narrowly than the totality of intersecting concerns biologists and philosophers (let alone other scholars) might have. The reasons for the success of the “new” philosophy of biology remain poorly understood. I reflect on what Dutch and Flemish, and, more generally, European (...) philosophers of biology could do to improve the situation of their discipline locally, regionally, and internationally, paying particular attention to the lessons to be learned from the “Science Wars.”. (shrink)

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

The discovery and ongoing investigation of microRNAs suggest important conceptual and methodological lessons for philosophers and historians of biology. This paper provides an account of miRNA research and the shift from viewing these tiny regulatory entities as minor curiosities to seeing them as major players in the post-transcriptional regulation of genes. Conceptually, the study of miRNAs is part of a broader change in understandings of genetic regulation, in which simple switch-like mechanisms were reinterpreted as aspects of complex cellular and genome-wide (...) processes. Among them are the activities of small RNAs, previously regarded as non-functional. Methodologically, the miRNA story suggests new ways of characterizing biological research that should prove helpful to philosophers of science who seek to develop more pluralistic, pragmatic models of scientific inquiry. miRNA research displays iterative movements between multiple modes of investigation that include not only the proposal and testing of hypotheses but also exploratory, technology-oriented and question-driven modes of research. As an exemplary story of scientific discovery and development, the miRNA case illustrates transitions from genetics to genomics and systems biology, and it shows how diverse configurations of research practice are related to major scientific advances. (shrink)

Systems biology is largely tributary to genomics and other “omic” disciplines that generate vast amounts of structural data. “Omics”, however, lack a theoretical framework that would allow using these data sets as such (rather than just tiny bits that are extracted by advanced data-mining techniques) to build explanatory models that help understand physiological processes. Systems biology provides such a framework by adding a dynamic dimension to merely structural “omics”. It makes use of bottom-up and top-down models. The former are based (...) on data about systems components, the latter on systems-level data. We trace back both modeling strategies (which are often used to delineate two branches of the field) to the modeling of metabolic and signaling pathways in the bottom-up case, and to biological cybernetics and systems theory in the top-down case. We then argue that three roots of systems biology must be discerned to account adequately for the structure of the field: pathway modeling, biological cybernetics, and “omics”. We regard systems biology as merging modeling strategies (supplemented by new mathematical procedures) from data-poor fields with data supply from a field that is quite deficient in explanatory modeling. After characterizing the structure of the field, we address some epistemological and ontological issues regarding concepts on which the top-down approach relies and that seem to us to require clarification. This includes the consequences of identifying modules in large networks without relying on functional considerations, the question of the “holism” of systems biology, and the epistemic value of the “systeome” project that aspires to become the cutting edge of the field. (shrink)

Synthetic biology is an increasingly high-profile area of research that can be understood as encompassing three broad approaches towards the synthesis of living systems: DNA-based device construction, genome-driven cell engineering and protocell creation. Each approach is characterized by different aims, methods and constructs, in addition to a range of positions on intellectual property and regulatory regimes. We identify subtle but important differences between the schools in relation to their treatments of genetic determinism, cellular context and complexity. These distinctions tie into (...) two broader issues that define synthetic biology: the relationships between biology and engineering, and between synthesis and analysis. These themes also illuminate synthetic biology's connections to genetic and other forms of biological engineering, as well as to systems biology. We suggest that all these knowledge-making distinctions in synthetic biology raise fundamental questions about the nature of biological investigation and its relationship to the construction of biological components and systems. (shrink)

Developmental systems theory (DST) expands the unit of replication from genes to whole systems of developmental resources, which DST interprets in terms of cycling developmental processes. Expansion seems required by DST's argument against privileging genes in evolutionary and developmental explanations of organic traits. DST and the expanded replicator brook no distinction between biological and cultural evolution. However, by endorsing a single expanded unit of inheritance and leaving the classical molecular notion of gene intact, DST achieves only a nominal reunification of (...) heredity and development. I argue that an alternative conceptualization of inheritance denies the classical opposition of genetics and development while avoiding the singularity inherent in the replicator concept. It also yields a new unit--the reproducer--which genuinely integrates genetic and developmental perspectives. The reproducer concept articulates the non-separability of "genetic" and "developmental" roles in units of heredity, development, and evolution. DST reformulated in terms of reproducers rather than replicators preserves an empirically interesting distinction between cultural and biological evolution. (shrink)

Synthetic biology is an umbrella term that covers a range of aims, approaches, and techniques. They are all brought together by common practices of analogizing, synthesizing, mechanicizing, and kludging. With a focus on kludging as the connection point between biology, engineering, and evolution, I show how synthetic biology’s successes depend on custom-built kludges and a creative, “make-it-work” attitude to the construction of biological systems. Such practices do not fit neatly, however, into synthetic biology’s celebration of rational design. Nor do they (...) straightforwardly embody Richard Feynman’s “last blackboard” statement that without creating something it cannot be understood. Reflecting further on the relationship between synthetic construction and knowledge making gives philosophy of science new avenues of insight into scientific practice. (shrink)

Complex Systems Biology approaches are here considered from the viewpoint of Robert Rosen’s (M,R)-systems, Relational Biology and Quantum theory, as well as from the standpoint of computer modeling. Realizability and Entailment of (M,R)-systems are two key aspects that relate the abstract, mathematical world of organizational structure introduced by Rosen to the various physicochemical structures of complex biological systems. Their importance for understanding biological function and life itself, as well as for designing new strategies for treating diseases such as cancers, is (...) pointed out. The roles played by multiple metastable states in the “continuous uphill flow of Life” supported through internal bioenergetic processes that are coupled to essential inflows are also discussed in relation to dynamic realizations of (M,R)-systems. Furthermore, the roles played by the underlying, many-valued, quantum logics and symbolic computations for ultra-complex biological systems are also briefly discussed. (shrink)

I begin by arguing that a consistent general naturalism must be understood in terms of methodological maxims rather than metaphysical doctrines. Some specific maxims are proposed. I then defend a generalized naturalism from the common objection that it is incapable of accounting for the normative aspects of human life, including those of scientific practice itself. Evolutionary naturalism, however, is criticized as being incapable of providing a sufficient explanation of categorical moral norms. Turning to the epistemological norms of science itself, particularly (...) those governing the empirical testing of specific models, I argue that these should be regarded as conditional rather than categorical and that, as such, can be given a naturalistic justification. The justification, however, is more cognitive than evolutionary. The historical development of science is found to be a better place for applying evolutionary ideas. After briefly considering the possibility of a naturalistic understanding of mathematics and logic, I turn to the problem of reconciling scientific realism with an evolutionary picture of scientific development. The solution, I suggest, is to understand scientific knowledge as being “perspectival” rather than absolutely objective. I first argue that scientific observation, whether by humans or instruments, is perspectival. This argument is extended to scientific theorizing which is regarded not as the formulation of universal laws of nature but as the construction of principles to be used in the construction of models to be applied to specific natural systems. The application of models, however, is argued to be not merely opportunistic but constrained by the methodological presumption that we live in a world with a definite causal structure even though we can understand it only from various perspectives. (shrink)

I characterize Wimsatt’s approach to philosophy of science as philosophy for science and then briefly consider a theme emerging from his work that informs just one of the many current developments in philosophy of biology that he inspired: scaffolding as a problem of mechanistic explanation for functionalists.

Bogen and Woodward characterized data as embedded in the context in which they are produced (‘local’) and claims about phenomena as retaining their significance beyond that context (‘nonlocal’). This view does not fit sciences such as biology, which successfully disseminate data via packaging processes that include appropriate labels, vehicles, and human interventions. These processes enhance the evidential scope of data and ensure that claims about phenomena are understood in the same way across research communities. I conclude that the degree of (...) locality of both data and claims about phenomena varies depending on the packaging used to make them travel and on the research setting in which they are used. †To contact the author, please write to: ESRC Centre for Genomics in Society, University of Exeter, Byrne House, St. Germans Road, EX4 4PJ Exeter, United Kingdom; e‐mail: [email protected]. (shrink)