Waddington redux: Simple abstract models and integrative biological explanations

Melinda Fagan Homepage

Melinda Bonnie Fagan
Assistant Professor of Philosophy
Rice University
(713) 348-2298
Presented in the Embryo Physics Course, February 6, 2013


The epigenetic landscape is a model of development, originally proposed by C. H. Waddington to visually explicate an integrated theory of genetics, development and evolution.  This simple, evocative model represents development as an undulating surface of hills and valleys.  Today, updated versions of Waddington’s landscape play significant, though distinct, roles in stem cell research and systems biology.  Both fields offer new and fruitful approaches to studying biological development.  But it is not clear how they should relate.  In stem cell biology, the predominant method is experimental manipulation of concrete cells and tissues.  Systems biology, in contrast, emphasizes mathematical modeling of cellular systems.  I argue that Waddington’s landscape model can help coordinate stem cell and systems approaches to yield integrated, ‘mechanistic’ explanations of cell development.  In this way, Waddington’s landscape can play an updated unificatory role.  I examine this model’s structure, representational assumptions, and uses in all three contexts, and argue that explanations of cell development require both mathematical models and concrete experiments.  On this view, the two approaches are interdependent, with mathematical models playing a crucial but circumscribed role in explanations of cell development. 




Melinda Bonnie Fagan is Assistant Professor of Philosophy at Rice University in Houston, Texas.  She has PhDs in Biological Sciences (Stanford University, 1998) and History and Philosophy of Science (Indiana University, Bloomington, 2007) and is the author of over twenty articles and book chapters on biology and philosophy of science.  Her research is on epistemology of scientific inquiry, focusing on relations between social aspects of our scientific practices and normative epistemic ideals (e.g., objectivity, justification, reliability).  Her first book, Philosophy of Stem Cell Biology: Knowledge in Flesh and Blood (Palgrave Macmillan, 2013), examines stem cell research from a philosophy of science approach.  Key topics include experimental evidence, causal explanation, model organisms, the role of the gene, scientific collaboration, and the rise of systems biology and post-genomic technologies.  She is currently beginning a new research project on scientific explanation, emphasizing the role of collaboration and joint action. 

Since 2007 she has taught undergraduate and graduate courses in Epistemology and Philosophy of Science at Rice University, Houston.  She is involved in interdisciplinary initiatives to expand participation of women in philosophy, to establish a research center in ‘Energy Humanities’ in Houston, and to explore links between the humanities, science and public policy.  She serves on the editorial board of Social Epistemology, the Financial Advisory Board of Rice’s Humanities Research Center, as a reviewer for the National Science Foundation, the Société de Philosophie des Sciences, and the Wellcome Trust.


I am a biologist-turned-philosopher of science, and my work focuses on the relation between those two fields.  I arrived in philosophy by the rather circuitous route of studying the biology of clonal organisms: first the population structure of Lonicera hirsuta (the hairy honeysuckle), then the histocompatibility response in Botryllus schlosseri (a colonial sea squirt).  The silliness of their common names was not a decisive factor in my choice of these organisms for study.  I was initially attracted, instead, by their novelty (to me) and vivid coloring.  But in the course of studying their composition and habits, I became increasingly troubled by discontinuities – between ‘textbook’ science and actual research; theoretical and experimental practices; the myriad uncertainties of ongoing inquiry and the solid reliability of established results.  By the time I had completed my dissertation (on the colorful botryllids), it was clear that my primary intellectual interests were at one remove, so to speak, from those of contemporary experimental biologists.  So I began to study philosophy, the proper home of the questions that troubled me.  These same questions are at the core of my research today: How is scientific knowledge related to experimental practice?  How do (or should) social interactions and values impact scientific knowledge?  What counts as scientific knowledge anyway – and on whose authority?  I investigate these and related questions by looking closely at areas of science I know well, and so bring these fields into closer contact with core debates in philosophy of science and social epistemology. 




3 responses to “Waddington redux: Simple abstract models and integrative biological explanations”

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    I’m sorry that I won’t be able to listen to your webinar because at the same time I’m teaching my graduate course entitled FROM THE CELL TO CANCER. I liked your biologist to philosopher translocation. I’d enjoy learning that many other biologists would have taken your turn. Please, send me your papers, though I’m rather skeptical about stem cells, an operational entity.


  2. Melinda,

    Enjoyed your presentation. I have two observations/ items for thought. The first are the parallels between epigenetic landscapes (Waddington) and so-called fitness landscapes (Wright) in evolutionary biology. In both cases, they are indeed highly conceptual — although fitness landscapes have been more explicitly tied to quantitative features of a population (e.g. measurements of fitness).

    Where fitness (and epigenetic) landscapes seem to be arbitrary, at least to me, is in characterizing the “genotype” (or “phenotype”). I would think that any such surface would contain an implicit metric, that of all possible combinations of a genotype (or phenotype) — even if it is categorical in nature.

    How this can be determined from experimental data (or even observables) is of course where these types of models become quite arbitrary — but by using the landscape metaphor one mush also accept that a set of formal relationships between “states” exist. Compare this with the use of energy landscapes in statistical physics, where the surface can be extrapolated from an energy function. We’re not dealing with physics here, but there’s some sort of conceptually advance here waiting to be discovered……

    The second observation is: what is the consequence of mapping from a tree (branching points in development) to a surface (the first few slides on Waddington’s approach)?

    From a data structures (CS) perspective, a class of structures called k-d trees are often used to represent highly complex surfaces. Could this approach be used to “revisit” the Waddington model with high-throughput data and
    modern computational techniques? Perhaps.

  3. I was ill the day of your lecture and would like to have copies of some of your papers that you are willing to share. I feel that you are in an important area of research – basicly sorting fact from fiction. The Anaotmy and Physiology I teach sometimes seems odd – not quite right. It is sometimes hard to say exactly what is wrong or right with some parts of it. Perhaps it is just incomplete.