Gain-of-function research and model organisms in biology.

So-called 'gain-of-function' (GOF) research is virological research that results in a virus substantially more virulent or transmissible than its wild antecedent. GOF research has been subject to ethical analysis in the past, but the methods of GOF research have to date been underexamined by philosophers in these analyses. Here, we examine the typical animal used in influenza GOF experiments, the ferret, and show how despite its longstanding use, it does not easily satisfy the desirable criteria for an animal model We then discuss the limitations of the ferret model, and how those epistemic limitations bear on ethical and policy questions around the risks and benefits of GOF research. We conclude with a reflection on how philosophy of science can contribute to ethical and policy debates around the risks, benefits and relative priority of life sciences research.

Whatever happened to reversion?

The idea of 'reversion' or 'atavism' has a peculiar history. For many authors in the late-nineteenth and early-twentieth centuries - including Darwin, Galton, Pearson, Weismann, and Spencer, among others - reversion was one of the central phenomena which a theory of heredity ought to explain. By only a few decades later, however, Fisher and others could look back upon reversion as a historical curiosity, a non-problem, or even an impediment to clear theorizing. I explore various reasons that reversion might have appeared to be a central problem for this first group of figures, focusing on their commitment to a variety of conceptual features of evolutionary theory; discuss why reversion might have then ceased to be an interesting phenomenon; and, finally, close with some more general thoughts about the death of scientific problems.

Of stirps and chromosomes: Generality through detail.

One claim found in the received historiography of the biometrical school (comprised primarily of Francis Galton, Karl Pearson, and W. F. R. Weldon) is that one of the biometricians' great flaws was their inability to look past their population-focused, statistical, gradualist understanding of evolutionary change - which led, in part, to their ignoring developments in cellular biology around 1900. I will argue, on the contrary, that the work of the biometricians was, from its earliest days, fundamentally concerned with connections between statistical patterns of inheritance and the underlying cellular features that gave rise to them. Such work remained current with contemporary knowledge of chromosomes, cytology, and development; in this article, I explore the first case. The biometricians were thus well positioned to understand the relationship between the patterns of Mendelian inheritance and the statistical distributions with which they primarily occupied themselves. Ignorance of this connection, then, is not the reason why they rejected Mendelism. Further, both Galton and Weldon - though each in their own unique way - decided to turn to biological detail as a way to better justify the generality of their statistical approaches to heredity. Perhaps paradoxically, then, for these biometricians, detail offered an approach to theoretical generality.

The early history of chance in evolution.

Work throughout the history and philosophy of biology frequently employs 'chance', 'unpredictability', 'probability', and many similar terms. One common way of understanding how these concepts were introduced in evolution focuses on two central issues: the first use of statistical methods in evolution (Galton), and the first use of the concept of "objective chance" in evolution (Wright). I argue that while this approach has merit, it fails to fully capture interesting philosophical reflections on the role of chance expounded by two of Galton's students, Karl Pearson and W.F.R. Weldon. Considering a question more familiar from contemporary philosophy of biology--the relationship between our statistical theories of evolution and the processes in the world those theories describe--is, I claim, a more fruitful way to approach both these two historical actors and the broader development of chance in evolution.

MTBindingSim: simulate protein binding to microtubules.

SUMMARY: Many protein-protein interactions are more complex than can be accounted for by 1:1 binding models. However, biochemists have few tools available to help them recognize and predict the behaviors of these more complicated systems, making it difficult to design experiments that distinguish between possible binding models. MTBindingSim provides researchers with an environment in which they can rapidly compare different models of binding for a given scenario. It is written specifically with microtubule polymers in mind, but many of its models apply equally well to any polymer or any protein-protein interaction. MTBindingSim can thus both help in training intuition about binding models and with experimental design. AVAILABILITY AND IMPLEMENTATION: MTBindingSim is implemented in MATLAB and runs either within MATLAB (on Windows, Mac or Linux) or as a binary without MATLAB (on Windows or Mac). The source code (licensed under the GNU General Public License) and binaries are freely available at http://mtbindingsim.googlecode.com. CONTACT: jphilip@nd.edu; cpence@nd.edu.

RLetters: A Web-Based Application for Text Analysis of Journal Articles.

While textual analysis of the journal literature is a burgeoning field, there is still a profound lack of user-friendly software for accomplishing this task. RLetters is a free, open-source web application which provides researchers with an environment in which they can select sets of journal articles and analyze them with cutting-edge textual analysis tools. RLetters allows users without prior expertise in textual analysis to analyze word frequency, collocations, cooccurrences, term networks, and more. It is implemented in Ruby and scripts are provided to automate deployment.

evoText: A new tool for analyzing the biological sciences.

We introduce here evoText, a new tool for automated analysis of the literature in the biological sciences. evoText contains a database of hundreds of thousands of journal articles and an array of analysis tools for generating quantitative data on the nature and history of life science, especially ecology and evolutionary biology. This article describes the features of evoText, presents a variety of examples of the kinds of analyses that evoText can run, and offers a brief tutorial describing how to use it.

Cognitive Phenotypes and the Evolution of Animal Decisions.

Despite the clear fitness consequences of animal decisions, the science of animal decision making in evolutionary biology is underdeveloped compared with decision science in human psychology. Specifically, the field lacks a conceptual framework that defines and describes the relevant components of a decision, leading to imprecise language and concepts. The 'judgment and decision-making' (JDM) framework in human psychology is a powerful tool for framing and understanding human decisions, and we apply it here to components of animal decisions, which we refer to as 'cognitive phenotypes'. We distinguish multiple cognitive phenotypes in the context of a JDM framework and highlight empirical approaches to characterize them as evolvable traits.

Military genomic testing: proportionality, expected benefits, and the connection between genotypes and phenotypes.

Mehlman and Li offer a framework for approaching the bioethical issues raised by the military use of genomics that is compellingly grounded in both the contemporary civilian and military ethics of medical research, arguing that military commanders must be bound by the two principles of paternalism and proportionality. I agree fully. But I argue here that this is a much higher bar than we may fully realize. Just as the principle of proportionality relies upon a thorough assessment of harms caused and military advantage gained, the use of genomic research, on Mehlman and Li's view, will require an accurate understanding of the connection between genotypes and phenotypes - accurate enough to ameliorate the risk undertaken by our armed forces in being subject to such research. Recent conceptual work in evolutionary theory and the philosophy of biology, however, renders it doubtful that such knowledge is forthcoming. The complexity of the relationship between genotypic factors and realized traits (the so-called 'G→P map') makes the estimation of potential military advantage, as well as potential harm to our troops, incredibly challenging. Such fundamental conceptual challenges call into question our ability to ever satisfactorily satisfy the demands of a sufficiently rigorous ethical standard.

"Describing our whole experience": the statistical philosophies of W. F. R. Weldon and Karl Pearson.

There are two motivations commonly ascribed to historical actors for taking up statistics: to reduce complicated data to a mean value (e.g., Quetelet), and to take account of diversity (e.g., Galton). Different motivations will, it is assumed, lead to different methodological decisions in the practice of the statistical sciences. Karl Pearson and W. F. R. Weldon are generally seen as following directly in Galton's footsteps. I argue for two related theses in light of this standard interpretation, based on a reading of several sources in which Weldon, independently of Pearson, reflects on his own motivations. First, while Pearson does approach statistics from this "Galtonian" perspective, he is, consistent with his positivist philosophy of science, utilizing statistics to simplify the highly variable data of biology. Weldon, on the other hand, is brought to statistics by a rich empiricism and a desire to preserve the diversity of biological data. Secondly, we have here a counterexample to the claim that divergence in motivation will lead to a corresponding separation in methodology. Pearson and Weldon, despite embracing biometry for different reasons, settled on precisely the same set of statistical tools for the investigation of evolution.

Nietzsche's aesthetic critique of Darwin.

Despite his position as one of the first philosophers to write in the "post-Darwinian" world, the critique of Darwin by Friedrich Nietzsche is often ignored for a host of unsatisfactory reasons. I argue that Nietzsche's critique of Darwin is important to the study of both Nietzsche's and Darwin's impact on philosophy. Further, I show that the central claims of Nietzsche's critique have been broadly misunderstood. I then present a new reading of Nietzsche's core criticism of Darwin. An important part of Nietzsche's response can best be understood as an aesthetic critique of Darwin, reacting to what he saw as Darwin having drained life of an essential component of objective aesthetic value. For Nietzsche, Darwin's theory is false because it is too intellectual, because it searches for rules, regulations, and uniformity in a realm where none of these are to be found - and, moreover, where they should not be found. Such a reading goes furthest toward making Nietzsche's criticism substantive and relevant. Finally, I attempt to relate this novel explanation of Nietzsche's critique to topics in contemporary philosophy of biology, particularly work on the evolutionary explanation of culture.