Explanation in classical population genetics

Journal ArticleThe recent literature in Philosophy; of biology has drawn attention to the different sorts of explanations proffered in the biological sciences--we have molecular, biomedical, and evolutionary explanations. Do these explanations all have a common structure or relation that they seek to capture? This paper will answer in the negative. I defend a pluralistic and pragmatic approach to explanation. Using examples from classical population genetics, I argue that formal demonstrations, and even strictly "mathematical truths," may serve as explanatory in different historical contexts

Strategies of model building in population genetics

Journal ArticleIn 1966, Richard Levins argued that there are different strategies in model building in population biology. In this paper, I reply to Orzack and Sober's (1993) critiques of Levins and argue that his view on modeling strategies apply also in the context of evolutionary genetics. In particular, I argue that there are different ways in which models are used to ask and answer questions about the dynamics of evolutionary change, prospectively and retrospectively, in classical versus molecular evolutionary genetics. Further, I argue that robustness analysis is a tool for, if not confirmation, then something near enough, in this discipline

What and How do Cancer Systems Biologists Explain?

In this article, we argue, first, that there are very different research projects that fall under the heading of “systems biology of cancer.” While they share some general features, they differ in their aims and theoretical commitments. Second, we argue that some explanations in systems biology of cancer are concerned with properties of signaling networks (such as robustness or fragility) and how they may play an important causal role in patterns of vulnerability to cancer. Further, some systems biological explanations are compelling illustrations of how “top-down” and “bottom-up” approaches to the same phenomena may be integrated

Sometimes You Ride the Pegasus, Sometimes You Take the Road: Mitchell on Laws in Biology

Mitchell’s philosophical contributions are part of an ongoing conversation among philosophers and scientists about laws and unification in biology, going back at least to Darwin. This article situates Mitchell in this conversation, explains why and how she has correctly guided us away from false idols, and engages several difficult questions she leaves open. I argue that there are different epistemic roles laws (or models describing lawlike regularities) play in biological inquiry. First, they play the role of “how possibly” explanations, akin to Herschel’s characterization of Whewell’s “a priori Pegasus,” and second, they provide descriptions of empirical regularities, akin to the “plain matter of fact roadster.

Chance in the Modern Synthesis

The modern synthesis in evolutionary biology is taken to be that period in which a consensus developed among biologists about the major causes of evolution, a consensus that informed research in evolutionary biology for at least a half century. As such, it is a particularly fruitful period to consider when reflecting on the meaning and role of chance in evolutionary explanation. Biologists of this period make reference to “chance” and loose cognates of “chance,” such as: “random,” “contingent,” “accidental,” “haphazard,” or “stochastic.” Of course, what an author might mean by “chance” in any specific context varies. In the following, we first offer a historiographical note on the synthesis. Second, we introduce five ways in which synthesis authors spoke about chance. We do not take these to be an exhaustive taxonomy of all possible ways in which chance meaningfully figures in explanations in evolutionary biology. These are simply five common uses of the term by biologists at this period. They will serve to organize our summary of the collected references to chance and the analysis and discussion of the following questions: • What did synthesis authors understand by chance? • How did these authors see chance operating in evolution? • Did their appeals to chance increase or decrease over time during the synthesis? That is, was there a “hardening” of the synthesis, as Gould claimed (1983)

What and How do Cancer Systems Biologists Explain?

In this article, we argue, first, that there are very different research projects that fall under the heading of “systems biology of cancer.” While they share some general features, they differ in their aims and theoretical commitments. Second, we argue that some explanations in systems biology of cancer are concerned with properties of signaling networks (such as robustness or fragility) and how they may play an important causal role in patterns of vulnerability to cancer. Further, some systems biological explanations are compelling illustrations of how “top-down” and “bottom-up” approaches to the same phenomena may be integrated

Going big by going small: trade-offs in microbiome explanations of cancer

Microbial factors have been implicated in cancer risk, disease progression, treatment and prevention. The key word, however, is “implicated.” Our aim in this paper is to map out some of the tensions between competing methods, goals, and standards of evidence in cancer research with respect to the causal role of microbial factors. We discuss an array of pragmatic and epistemic trade-offs in this research area: prioritizing coarse-grained versus fine-grained explanations of the roles of microbiota in cancer; explaining general versus specific cancer targets; studying model organisms versus human patients; and understanding and explaining cancer versus developing diagnostic tools and treatments. In light of these trade-offs and the distinctive complexity and heterogeneity on both sides of the microbiome-cancer relationship, we suggest that it would be more productive and intellectually honest to frame much of this work, at least currently, in terms of generating causal hypotheses to investigate further. Claims of established causal connections between the microbiome and cancer are in many cases overstated. We also discuss the value of “black boxing” microbial causal variables in this research context and draw some general cautionary lessons for ongoing discussions of microbiomes and cancer

The Rise and Fall of the Adaptive Landscape?

The discussion of the adaptive landscape in the philosophical literature appears to be divided along the following lines. On the one hand, some claim that the adaptive landscape is either “uninterpretable” or incoherent. On the other hand, some argue that the adaptive landscape has been an important heuristic, or tool in the service of explaining, as well as proposing and testing hypotheses about evolutionary change. This paper attempts to reconcile these two views