The chemical characterization of the substance responsible for the phenomenon of “transformation” of pneumococci was presented in the now famous 1944 paper by Avery, MacLeod, and McCarty. Reception of this work was mixed. Although interpreting their results as evidence that deoxyribonucleic acid (DNA) is the molecule responsible for genetic changes was, at the time, controversial, this paper has been retrospectively celebrated as providing such evidence. The mixed and changing assessment of the evidence presented in the paper was due to the (...) work’s interpretive flexibility – the evidence was interpreted in various ways, and such interpretations were justified given the neophytic state of molecular biology and methodological limitations of Avery’s transformation studies. I argue that the changing context in which the evidence presented by Avery’s group was interpreted partly explains the vicissitudes of the assessments of the evidence. Two less compelling explanations of the reception are a myth-making account and an appeal to the wartime historical context of its publication. (shrink)

The philosophical debate around the impact of machine learning in science is often framed in terms of a choice between AI and classical methods as mutually exclusive alternatives involving difficult epistemological trade-offs. A common worry regarding machine learning methods specifically is that they lead to opaque models that make predictions but do not lead to explanation or understanding. Focusing on the field of molecular biology, I argue that in practice machine learning is often used with explanatory aims. More specifically, I (...) argue that machine learning can be tightly integrated with other, more traditional, research methods and in a clear sense can contribute to insight into the causal processes underlying phenomena of interest to biologists. One could even say that machine learning is not the end of theory in important areas of biology, as has been argued, but rather a new beginning. I support these claims with a detailed discussion of a case study involving gene regulation by microRNAs. (shrink)

Ian Hacking’s Representing and Intervening is often credited as being one of the first works to focus on the role of experimentation in philosophy of science, catalyzing a movement which is sometimes called the “philosophy of experiment” or “new experimentalism”. In the 1980s, a number of other movements and scholars also began focusing on the role of experimentation and instruments in science. Philosophical study of experimentation has thus seemed to be an invention of the 1980s whose central figure is Hacking. (...) This article aims to assess this historical claim, made by Hacking himself as well as others. It does so first by highlighting how a broader perspective on the history of philosophy reveals this invention narrative to be incorrect, since experimentation was a topic of interest for earlier philosophers. Secondly, the article evaluates a revision of this historical claim also made by some philosophers of experiment: the rediscovery narrative, which frames Hacking and others as having rediscovered the work of these earlier authors. This second narratives faces problems as well. Therefore we develop a third narrative which we call the contextualist narrative. Rather than considering experimentation in an essentialist manner as a fixed research object that is either present or not in the work of specific authors, experimentation should be addressed through a narrative that asks in what way it becomes a philosophical problem for certain authors and for what purpose. Such contextualization enables a repositioning of Hacking’s philosophy of experiment in relation to the specific debates in which he intervened, such as the realism-antirealism debate, the Science Wars and the debate on incommensurability. (shrink)

Model organisms are a living form of scientific models. Despite the widespread use of model organisms in scientific research, the actual representational relationship between model organisms and their target species is often poorly characterized in the context of cross-species research. Many model organisms do not represent the target species adequately, let alone accurately. This is partly due to the complex and emergent life phenomena in the organism, and partly due to the fact that a model organism is always taken to (...) represent a broad range of diverse organisms. More often than not, model organisms are taken as a reference point for an extrapolation to be made to the unknown characteristics of other species. I propose to view model organisms as analogue simulators which represent the emergent phenomenon in the context of cross-species research. A model organism represents a wide range of species by simulating their molecular microstates which underlie various emergent phenomena. I show that although model organisms represent the target species inadequately at many levels of complexity, they have epistemic values as a simulator in virtue of which the emergent phenomenon can be modeled dynamically, a virtue that is hardly attainable by non-dynamic models. (shrink)

This paper explores multiple experimental interventions in molecular biology. By “multiple,” we mean that molecular biologists often use different modes of experimental interventions in a series of experiments for one and the same subject. In performing such a series of experiment, scientists may use different modes of interventions to realize plural goals such as testing given hypotheses and exploring novel phenomena. In order to illustrate this claim, we develop a framework of multiple modes of experimental interventions to analyze a series (...) of experiments for a single subject. Our argument begins with a brief characterization of Craver and Darden’s taxonomy of experiments, because the taxonomy they have made implies various modes of interventions. We propose to extract two interventional directions and two interventional effects from their taxonomy as the basis of classification. The vertical or inter-level direction means that an intervention is performed between different levels of organization and the horizontal or inter-stage direction means that an intervention is performed between different stages of a mechanism. Interventions may produce an excitatory or an inhibitory effect. As a consequence, we can classify modes of interventions according to different directions and effects. We illustrate our claims by doing a case study of the PaJaMo experiment, which is a series of experiments for a single subject. The final goal in this paper is to provide a taxonomy of characteristics of experimentation in which the PaJaMo experiment is adequately located. (shrink)

Review essay of How to do science with models. A philosophical primer. Springer briefs in philosophy, Axel Gelfert., 129, Price € 49,99 softcover, ISBN: 978-3-319-27954-1.

Experimentation represents today a ‘hot’ topic in computing. If experiments made with the support of computers, such as computer simulations, have received increasing attention from philosophers of science and technology, questions such as “what does it mean to do experiments in computer science and engineering and what are their benefits?” emerged only recently as central in the debate over the disciplinary status of the discipline. In this work we aim at showing, also by means of paradigmatic examples, how the traditional (...) notion of controlled experiment should be revised to take into account a part of the experimental practice in computing along the lines of experimentation as exploration. Taking inspiration from the discussion on exploratory experimentation in the philosophy of science—experimentation that is not theory-driven—we advance the idea of explorative experiments that, although not new, can contribute to enlarge the debate about the nature and role of experimental methods in computing. In order to further refine this concept we recast explorative experiments as socio-technical experiments, that test new technologies in their socio-technical contexts. We suggest that, when experiments are explorative, control should be intended in a posteriori form, in opposition to the a priori form that usually takes place in traditional experimental contexts. (shrink)

ArgumentIn the theory-dominated view of scientific experimentation, all relations of theory and experiment are taken on a par; namely, that experiments are performed solely to ascertain the conclusions of scientific theories. As a result, different aspects of experimentation and of the relations of theory to experiment remain undifferentiated. This in turn fosters a notion of theory-ladenness of experimentation (TLE) that is toocoarse-grainedto accurately describe the relations of theory and experiment in scientific practice. By contrast, in this article, I suggest that (...) TLE should be understood as anumbrella conceptthat has different senses. To this end, I introduce a three-fold distinction among the theories of high-energy particle physics (HEP) as background theories, model theories, and phenomenological models. Drawing on this categorization, I contrast two types of experimentation, namely, “theory-driven” and “exploratory” experiments, and I distinguish between the “weak” and “strong” senses of TLE in the context of scattering experiments from the history of HEP. This distinction enables identifying the exploratory character of the deep-inelastic electron-proton scattering experiments – performed at the Stanford Linear Accelerator Center (SLAC) between the years 1967 and 1973 – thereby shedding light on a crucial phase of the history of HEP, namely, the discovery of “scaling,” which was the decisive step towards the construction of quantum chromo-dynamics as a gauge theory of strong interactions. (shrink)

This chapter offers a review of standard views about the requirements for natural selection to shape evolution and for the sorts of ‘units’ on which selection might operate. It then summarizes traditional arguments for genic selectionism, i.e., the view that selection operates primarily on genes (e.g., those of G. C. Williams, Richard Dawkins, and David Hull) and traditional counterarguments (e.g., those of William Wimsatt, Richard Lewontin, and Elliott Sober, and a diffuse group based on life history strategies). It then offers (...) a series of responses to the arguments, based on more contemporary considerations from molecular genetics, offered by Carmen Sapienza. A key issue raised by Sapienza concerns the degree to which a small number of genes might be able to control much of the variation relevant to selection operating on such selectively critical organs as hearts. The response to these arguments suggests that selection acts on many levels at once and that sporadic selection, acting with strong effects, can act successively on different key traits (and genes) while maintaining a balance among many potentially conflicting demands faced by organisms within an evolving lineage. (shrink)

The 1980s, it is often claimed, was the decade when experimentation finally became a philosophical topic. This was the responsibility, the claim continues, of one particular movement within philosophy of science, called “new experimentalism.” The aim of this article is to complicate this historical narrative. We argue that in the 1980s, the study of experimentation was carried out not by one movement with one particular aim but rather in a diverse and open-ended way by people with different aims and backgrounds. (...) We then argue that from the late 1990s onward, this diversity disappeared and made room for disciplinary divisions—questions concerning experimentation became philosophical, others sociological, and so on. The reason for this, we claim, was that science and technology studies, philosophy of technology, and philosophy of science took over aspects of the 1980s study of experimentation. In this way, we argue, these elements became institutionalized, whereas others were forgotten. The importance of this process of institutionalization is illustrated by means of a discussion of other, similar approaches to the philosophy of experimentation that have not been able to ensure continuity because they did not find an institutional home. (shrink)

Philosophers of science diverge on the question what drives the growth of scientific knowledge. Most of the twentieth century was dominated by the notion that theories propel that growth whereas experiments play secondary roles of operating within the theoretical framework or testing theoretical predictions. New experimentalism, a school of thought pioneered by Ian Hacking in the early 1980s, challenged this view by arguing that theory-free exploratory experimentation may in many cases effectively probe nature and potentially spawn higher evidence-based theories. Because (...) theories are often powerless to envisage workings of complex biological systems, theory-independent experimentation is common in the life sciences. Some such experiments are triggered by compelling observation, others are prompted by innovative techniques or instruments, whereas different investigations query big data to identify regularities and underlying organizing principles. A distinct fourth type of experiments is motivated by a major question. Here I describe two question-guided experimental discoveries in biochemistry: the cyclic adenosine monophosphate mediator of hormone action and the ubiquitin-mediated system of protein degradation. Lacking underlying theories, antecedent data bases, or new techniques, the sole guides of the two discoveries were respective substantial questions. Both research projects were similarly instigated by theory-free exploratory experimentation and continued in alternating phases of results-based interim working hypotheses, their examination by experiment, provisional hypotheses again, and so on. These two cases designate theory-free, question-guided, stepwise biochemical investigations as a distinct subtype of the new experimentalism mode of scientific enquiry. (shrink)

To explain their role in discovery and contrast them with theory-driven research, philosophers of science have characterized exploratory experiments in terms of what they lack: namely, that they lack direction from what have been called “local theories” of the target system or object under investigation. I argue that this is incorrect: it’s not whether or not there is direction from a local theory that matters, but instead how such a theory is used to direct an experiment that matters. Appealing to (...) contemporary exploratory experiments that involve the use of experimental techniques—specifically, examples where scientists explore the interaction of neural activity and human behavior by magnetically stimulating brains—I argue that local theories of a target system can inform auxiliary hypotheses in exploratory experiments, which direct these experiments. These examples illustrate how local theories can direct the exploration of target systems where researchers do not aim to evaluate these theories. (shrink)

Observation and experiment as categories for analysing scientific practice have a long pedigree in writings on science. There has, however, been little attempt to delineate observation and experiment with respect to analysing scientific practice; in particular, scientific experimentation, in a systematic manner. Someone who has presented a systematic account of observation and experiment as categories for analysing scientific experimentation is Ian Hacking. In this paper, I present a detailed analysis of Hacking’s observation versus experiment account. Using a range of cases (...) from various fields of scientific enquiry, I argue that the observation versus experiment account is not an adequate framework for delineating scientific experimentation in a systematic manner. (shrink)

1. Overview and organizing themes 2. Historical Review: Aristotle to Mill 3. Logic of method and critical responses 3.1 Logical constructionism and Operationalism 3.2. H-D as a logic of confirmation 3.3. Popper and falsificationism 3.4 Meta-methodology and the end of method 4. Statistical methods for hypothesis testing 5. Method in Practice 5.1 Creative and exploratory practices 5.2 Computer methods and the ‘third way’ of doing science 6. Discourse on scientific method 6.1 “The scientific method” in science education and as seen (...) by scientists 6.2 Privileged methods and ‘gold standards’ 6.3 Scientific method in the court room 6.4 Deviating practices 7. Conclusion Bibliography Academic Tools Other Internet Resources Related Entries . (shrink)

The life sciences are said to be in the midst of a replication crisis because a majority of published results are irreproducible, and scientists rarely replicate existing data. Here I argue that point 2 of this assessment is flawed because there is a hitherto unidentified form of replication in the experimental life sciences, which I call ‘microreplications’. Using a case study from biochemistry, I illustrate how MRs depend on a key element of experimentation, namely, experimental controls. I end by reflecting (...) on what MRs mean for the broader debate about the replication crisis. (shrink)

Exploratory inquiry has difficulty attracting research funding because funding agencies have little sense of how to detect good science in exploratory contexts. After documenting and explaining the focus on hypothesis testing among a variety of institutions responsible for distinguishing between good and bad science, I analyze the NIH grant review process. I argue that a good explanation for the focus on hypothesis testing—at least at the level of science funding agencies—is the fact that hypothesis-driven research is relatively easy to appraise. (...) I then explore one method by which we might gauge the epistemic merits of different styles of inquiry. (shrink)

My aim in this article is to introduce readers to the topic of exploratory experimentation and briefly explain how the three articles that follow, by Richard Burian, Kevin Elliott, and Maureen O'Malley, advance our understanding of the nature and significance of exploratory research. I suggest that the distinction between exploratory and theory-driven experimentation is multidimensional and that some of the dimensions are continuums. I point out that exploratory experiments are typically theory-informed even if they are not theory-driven. I also distinguish (...) between research programs and experiments. Research programs that are largely exploratory, such as the ones discussed in these case studies, can involve both exploratory and theory-driven experimentation. (shrink)

The experimental practice in contemporary molecular biology oscillates between the creativity of the researcher in tinkering with the experimental system, and the necessity of standardization of methods of inquiry. Experimental procedures, when standardized in lab protocols, might definitely be seen as actual recipes. Considering these protocols as recipes can help us understand some epistemological characteristics of current practice in molecular biology. On the one hand, protocols represent a common ground, i.e. the possibility of reproducibility, which constitutes one of the essential (...) properties for contemporary science to define an actual discovery. At the same time, however, protocols are flexible enough to be adapted by the individual researcher (within a space of maneuver given by the experimental system and by the practices that each individual discipline gives to itself) to his/her specific needs. These variations, just like the recipes, remind us that the legitimacy of an experimental practice, involves both objective and subjective constraints and it is articulated on a fuzzy background rather than a rigid and clear context. Moreover, looking at experiments according to this perspective can provide a key to understanding how different forms of science (which adopt different methodologies but which investigate the same phenomena), such as computational biology, are precisely different in the use of a different “cookbook”.Indeed, given the procedural/operational realism of biologists towards phenomena, the clash of different procedures has opened a discussion also about the nature and the meaning of the obtained results. Thus, according to the recipe-perspective that, the methodological struggle over the nature of biological phenomena (and their ways of discovery) among scientists, might be seen as a not always explicit, epistemological debate, however coming from the practice of science itself. (shrink)

Along three measurements at the Large Hadron Collider (LHC), a high energy particle accelerator, we analyze procedures and consequences of exploratory experimentation (EE). While all of these measurements fulfill the requirements of EE: probing new parameter spaces, being void of a target theory and applying a broad range of experimental methods, we identify epistemic differences and suggest a classification of EE. We distinguish classes of EE according to their respective goals: the exploration where an established global theory cannot provide the (...) details of a local phenomenon, exploration of an astonishing discovery and exploration to find a new entity. We find that these classes also differ with respect to the existence of an identifiable target and their impact on the background theory. The characteristics distinguish EE from other kinds of experimentation, even though these different kinds have not yet been systematically studied. The formal rigor and precision of LHC physics facilitates to analyze concept formation in its early state. In particular we emphasize the importance for nil–results for conceptualization and argue that conceptualization can also be achieved from nil–results only. (shrink)

It is now well-appreciated by philosophers that contemporary large-scale ‘-omics’ studies in biology stand in non-trivial relationships to more orthodox hypothesis-driven approaches. These relationships have been clarified by Ratti (2015); however, there remains much more to be said regarding how an important field of genomics cited in that work—‘genome-wide association studies’ (GWAS)—fits into this framework. In the present article, we propose a revision to Ratti’s framework more suited to studies such as GWAS. In the process of doing so, we introduce (...) to the philosophical literature novel exploratory experiments in (phospho)proteomics, and demonstrate how these experiments interplay with the above considerations. (shrink)

The discovery of RNA interference in 1998 has made a lasting impact on biological research. Identifying the regulatory role of small RNAs changed the modes of molecular biological inquiry as well as biologists' understanding of genetic regulation. This article examines the early years of small RNA biology's success story. I query which factors had to come together so that small RNA research came into life in the blink of an eye. I primarily look at scientific repertoires as facilitators of rapid (...) scientific change. I show that for a short period of time, between the years 1998 and 2002, different model organism communities, investigative strategies, technological innovations, and research interests could be successfully aligned to take small RNA research off the ground. I discuss how the keystone discoveries were situated in specific experimental traditions and what strategies were employed to establish these discoveries as more general phenomena. Providing thus a practice-based approach of rapid scientific change, I ask how to relate the change in propositional bits of scientific knowledge with changes in scientific practice. (shrink)

In this paper, I propose an account that accommodates the possibility of experimentation being exploratory in cases where the procedures necessary to plan and perform an experiment are dependent on the theoretical accounts of the phenomena under investigation. The present account suggests that experimental exploration requires the implementation of an exploratory procedure that serves to extend the range of possible outcomes of an experiment, thereby enabling it to pursue its objectives. Furthermore, I argue that the present account subsumes the notion (...) of exploratory experimentation, which is often attributed in the relevant literature to the works of Friedrich Steinle and Richard Burian, as a particular type of experimental exploration carried out in the special cases where no well-formed theoretical framework of the phenomena under investigation exists. I illustrate the present account in the context of the ATLAS experiment at CERN’s Large Hadron Collider, where the long-sought Higgs boson has been discovered in 2012. I argue that the data selection procedure carried out in the ATLAS experiment illustrates an exploratory procedure in the sense suggested by the present account. I point out that this particular data selection procedure is theory-laden in that its implementation is crucially dependent on the theoretical models of high energy particle physics which the ATLAS experiment is aimed to test. However, I argue that the foregoing procedure is not driven by the above-mentioned theoretical models, but rather by a particular data selection strategy. I conclude that the ATLAS experiment illustrates that, contrary to what previous studies have suggested, there are cases of experimentation in which exploration serves to test theoretical predictions and that theory-ladenness plays an essential role in experimentation being exploratory. (shrink)

We trace the history of the Modern Evolutionary Synthesis, and of genetic Darwinism generally, with a view to showing why, even in its current versions, it can no longer serve as a general framework for evolutionary theory. The main reason is empirical. Genetical Darwinism cannot accommodate the role of development (and of genes in development) in many evolutionary processes. We go on to discuss two conceptual issues: whether natural selection can be the “creative factor” in a new, more general framework (...) for evolutionary theorizing; and whether in such a framework organisms must be conceived as self-organizing systems embedded in self-organizing ecological systems. (shrink)

Computational modeling is one of the primary approaches to constructing protein–protein interfaces in the laboratory. The algorithm-driven computational protein design has been successfully applied to the construction of functional proteins with improved binding affinity and increased thermostability. It is intriguing how a computational protein modeling approach can construct and shape the reality of new functional proteins from scratch. I articulate an account of abstraction and exploration-driven strategies in this computational endeavor. I aim to show that how a computational modelling approach, (...) which is laden with mathematics and algorithms, can have a constructive force on the target protein. (shrink)