This collection of revised and new essays argues that biology is an autonomous science rather than a branch of the physical sciences. Ernst Mayr, widely considered the most eminent evolutionary biologist of the 20th century, offers insights on the history of evolutionary thought, critiques the conditions of philosophy to the science of biology, and comments on several of the major developments in evolutionary theory. Notably, Mayr explains that Darwin's theory of evolution is actually five separate theories, each with its own (...) history, trajectory and impact. Ernst Mayr, commonly referred to as the "Darwin of the 20th century" and listed as one of the top 100 scientists of all-time, is Professor Emeritus at Harvard University. What Makes Biology Unique is the 25th book he has written during his long and prolific career. His recent books include This is Biology: The Science of the Living World (Belknap Press, 1997) and What Evolution Is (Basic Books, 2002). (shrink)

The so-called "adaptationism" of mainstream evolutionary biology has been criticized from a variety of sources. One, which has received relatively little philosophical attention, is developmental biology. Developmental constraints are said to be neglected by adaptationists. This paper explores the divergent methodological and explanatory interests that separate mainstream evolutionary biology from its embryological and developmental critics. It will focus on the concept of constraint itself; even this central concept is understood differently by the two sides of the dispute.

Here I present and discuss a model that, among other things, appears able to describe the dynamics of cancer cell origin from the perspective of stable and unstable gene expression profiles. In identifying suchaberrantgene expression profiles as lying outside the normal stable states attracted through development and normal cell differentiation, the hypothesis explains why cancer cells accumulate mutations, to which they are not robust, and why these mutations create a new stable state far from the normal gene expression profile space. (...) Such cells are in strong contrast with normal cell types that appeared as an attractor state in the gene expression dynamical system under cell‐cell interaction and achieved robustness to noise through evolution, which in turn also conferred robustness to mutation. In complex gene regulation networks, otheraberrantcellular states lacking such high robustness are expected to remain, which would correspond to cancer cells. (shrink)

ORIGIN OF SPECIES. INTRODUCTION. When on board HMS 'Beagle,' as naturalist, I was ranch struck with certain facts in the distribution of the organic beings ...

... Difficulty of distinguishing between Varieties and Species — Origin of Domestic ... and Origin— Principle of Selection anciently followed, its Effects— ...

Mutational robustness facilitates evolutionary innovations. Gene duplications are unique kinds of mutations, in that they generally increase such robustness. The frequent association of gene duplications in regulatory networks with evolutionary innovation is thus a special case of a general mechanism linking innovation to robustness. The potential power of this mechanism to promote evolutionary innovations on large time scales is illustrated here with several examples. These include the role of gene duplications in the vertebrate radiation, flowering plant evolution and heart development, (...) which encompass some of the most striking innovations in the evolution of life. BioEssays 30:367–373, 2008. © 2008 Wiley Periodicals, Inc. (shrink)

An increasing number of biologists are expressing discontent with the prevailing theory of neo-Darwinism. In particular, the tendency of neo-Darwinians to adopt genetic determinism and atomistic notions of both genes and organisms is seen as grossly unfair to the body of developmental theory. One faction of dissenteers, the Process Structuralists, take their inspiration from the rational morphologists who preceded Darwin. These neo-rationalists argue that a mature biology must possess universal laws and that these generative laws should be sought within organismal (...) development. Such a rational biology will only be possible once the neo-Darwinian paradigm, with its reliance on inherently stochastic processes, is overthrown.To facilitate this revolution, process structuralism launches a broad attack on the theoritical adequacy of its opponent. It is charged that neo-Darwinism is untestable and therefore its hypotheses are nothing more than adaptive stories. Further, the lamentable tendencies toward genetic determinism and atomism by modern biologists is seen as the inescapable consequences of adopting the neo-Darwinian outlook. (shrink)

Recent work on self organization promises an explanation of complex order which is independent of adaptation. Self-organizing systems are complex systems of simple units, projecting order as a consequence of localized and generally nonlinear interactions between these units. Stuart Kauffman offers one variation on the theme of self-organization, offering what he calls a ``statistical mechanics'' for complex systems. This paper explores the explanatory strategies deployed in this ``statistical mechanics,'' initially focusing on the autonomy of statistical explanation as it applies in (...) evolutionary settings and then turning to Kauffman's analysis. Two primary morals emerge as a consequence of this examination: first, the view that adaptation and self-organization should be seen as competing theories or models is misleading and simplistic; and second, while we need a synthesis treating self-organization and adaptation as geared toward different problems, at different levels of organization, and deploying different methods, we do not yet have such a synthesis. (shrink)

When two populations of cells within a tissue mass differ from one another in magnitude or type of intercellular adhesions, a boundary can form within the tissue, across which cells will fail to mix. This phenomenon may occur regardless of the identity of the molecules that mediate cell adhesion. If, in addition, a choice between the two adhesive states is regulated by a molecule the concentration of which is periodic in space, or in time, then alternating bands of non‐mixing tissue, (...) or segments, can form. But temporal or spatial periodicities in concentration will tend to arise for any molecule that is positively autoregu‐latory. It is therefore proposed that segmentation is a ‘generic’ property of metazoan organisms, and that metamerism would be expected to have emerged numerous times during evolution. A simple model of segmentation, based solely on differential adhesion and periodic regulation of adhesion, can account for segment properties as disparate as those seen in long and short germ band insects, and for diverse experimental results on boundary regeneration in the chick hind brain and the insect cuticle. It is suggested that the complex, multicom‐ponent segment‐forming systems found in contemporary organisms (e.g., Drosophila) are the products of evolutionary recruitment of molecular cues such as homeobox gene products, that increase the reliability and stability of metameric patterns originally templated by generic self‐organizing properties of tissues. (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 importation of computational methods into biology is generating novel methodological strategies for managing complexity which philosophers are only just starting to explore and elaborate. This paper aims to enrich our understanding of methodology in integrative systems biology, which is developing novel epistemic and cognitive strategies for managing complex problem-solving tasks. We illustrate this through developing a case study of a bimodal researcher from our ethnographic investigation of two systems biology research labs. The researcher constructed models of metabolic and cell-signaling (...) pathways by conducting her own wet-lab experimentation while building simulation models. We show how this coupling of experiment and simulation enabled her to build and validate her models and also triangulate and localize errors and uncertainties in them. This method can be contrasted with the unimodal modeling strategy in systems biology which relies more on mathematical or algorithmic methods to reduce complexity. We discuss the relative affordances and limitations of these strategies, which represent distinct opinions in the field about how to handle the investigation of complex biological systems. (shrink)

Our understanding of how evolution acts on biological networks remains patchy, as is our knowledge of how that action is best identified, modelled and understood. Starting with network structure and the evolution of protein–protein interaction networks, we briefly survey the ways in which network evolution is being addressed in the fields of systems biology, development and ecology. The approaches highlighted demonstrate a movement away from a focus on network topology towards a more integrated view, placing biological properties centre‐stage. We argue (...) that there remains great potential in a closer synergy between evolutionary biology and biological network analysis, although that may require the development of novel approaches and even different analogies for biological networks themselves. (shrink)

We argue that dynamical and mathematical models in systems and cognitive neuro- science explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phe- nomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models including the Haken-Kelso-Bunz model of bimanual coordination and the difference-of-Gaussians model of visual receptive fields are (...) explored. (shrink)

The Neo‐Darwinian concept of natural selection is plausible when one assumes a straightforward causation of phenotype by genotype. However, such simple 1:1 mapping must now give place to the modern concepts of gene regulatory networks and gene expression noise. Both can, in the absence of genetic mutations, jointly generate a diversity of inheritable randomly occupied phenotypic states that could also serve as a substrate for natural selection. This form of epigenetic dynamics challenges Neo‐Darwinism. It needs to incorporate the non‐linear, stochastic (...) dynamics of gene networks. A first step is to consider the mathematical correspondence between gene regulatory networks and Waddington's metaphoric ‘epigenetic landscape’, which actually represents the quasi‐potential function of global network dynamics. It explains the coexistence of multiple stable phenotypes within one genotype. The landscape's topography with its attractors is shaped by evolution through mutational re‐wiring of regulatory interactions – offering a link between genetic mutation and sudden, broad evolutionary changes. (shrink)

The stunning possibility of “reprogramming” differentiated somatic cells to express a pluripotent stem cell phenotype (iPS, induced pluripotent stem cell) and the “ground state” character of pluripotency reveal fundamental features of cell fate regulation that lie beyond existing paradigms. The rarity of reprogramming events appears to contradict the robustness with which the unfathomably complex phenotype of stem cells can reliably be generated. This apparent paradox, however, is naturally explained by the rugged “epigenetic landscape” with valleys representing “preprogrammed” attractor states that (...) emerge from the dynamical constraints of the gene regulatory network. This article provides a pedagogical primer to the fundamental principles of gene regulatory networks as integrated dynamic systems and reviews recent insights in gene expression noise and fate determination, thereby offering a formal framework that may help us to understand why cell fate reprogramming events are inherently rare and yet so robust. (shrink)

To explain the phenomena in the world of our experience, to answer the question “why?” rather than only the question “what?”, is one of the foremost objectives of all rational inquiry; and especially, scientific research in its various branches strives to go beyond a mere description of its subject matter by providing an explanation of the phenomena it investigates. While there is rather general agreement about this chief objective of science, there exists considerable difference of opinion as to the function (...) and the essential characteristics of scientific explanation. In the present essay, an attempt will be made to shed some light on these issues by means of an elementary survey of the basic pattern of scientific explanation and a subsequent more rigorous analysis of the concept of law and of the logical structure of explanatory arguments. (shrink)

A number of philosophers and ‘evolutionary psychologists’ have argued that attacks on adaptationism in contemporary biology are misguided. These thinkers identify anti-adaptationism with advocacy of non-adaptive modes of explanation. They overlook the influence of anti-adaptationism in the development of more rigorous forms of adaptive explanation. Many biologists who reject adaptationism do not reject Darwinism. Instead, they have pioneered the contemporary historical turn in the study of adaptation. One real issue which remains unresolved amongst these methodological advances is the nature of (...) ‘phylogenetic inertia’. To what extent is an adaptive explanation needed for the persistence of a trait as well as its origin? (shrink)

In this paper I offer an analysis of causation based upon a theory of mechanisms-complex systems whose internal parts interact to produce a system's external behavior. I argue that all but the fundamental laws of physics can be explained by reference to mechanisms. Mechanisms provide an epistemologically unproblematic way to explain the necessity which is often taken to distinguish laws from other generalizations. This account of necessity leads to a theory of causation according to which events are causally related when (...) there is a mechanism that connects them. I present reasons why the lack of an account of fundamental physical causation does not undermine the mechanical account. (shrink)

Stem cell biology and systems biology are two prominent new approaches to studying cell development. 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. For scientists and philosophers interested in development, an important question arises: how should the two approaches relate? This essay proposes an answer, using the model of Waddington’s landscape to triangulate between stem cell and systems approaches. This simple abstract model represents (...) development as an undulating surface of hills and valleys. Originally constructed by C. H. Waddington to visually explicate an integrated theory of genetics, development and evolution, the landscape model 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. (shrink)

An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent (...) explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)

At Home in the Universe presents and extends the intellectual core ofKauffman's earlier book The Origins of Order (OUP 1993) for any intelligentgeneral reader can understand and appreciate. The reader is very effectivelyinvited into Kauffman's vision and thought processes, in one of the moreexhilarating and important books of popular science.

In the six decades since the publication of Julian Huxley's Evolution: The Modern Synthesis, spectacular empirical advances in the biological sciences have been accompanied by equally significant developments within the core theoretical framework of the discipline. As a result, evolutionary theory today includes concepts and even entire new fields that were not part of the foundational structure of the Modern Synthesis. In this volume, sixteen leading evolutionary biologists and philosophers of science survey the conceptual changes that have emerged since Huxley's (...) landmark publication, not only in such traditional domains of evolutionary biology as quantitative genetics and paleontology but also in such new fields of research as genomics and EvoDevo. Most of the contributors to Evolution—The Extended Synthesis accept many of the tenets of the classical framework but want to relax some of its assumptions and introduce significant conceptual augmentations of the basic Modern Synthesis structure—just as the architects of the Modern Synthesis themselves expanded and modulated previous versions of Darwinism. This continuing revision of a theoretical edifice the foundations of which were laid in the middle of the nineteenth century—the reexamination of old ideas, proposals of new ones, and the synthesis of the most suitable—shows us how science works, and how scientists have painstakingly built a solid set of explanations for what Darwin called the "grandeur" of life. (shrink)

Carl Craver investigates what we are doing when we sue neuroscience to explain what's going on in the brain.

As Aristotle stated, scientific explanation is based on deductive argument--yet, Wesley C. Salmon points out, not all deductive arguments are qualified explanations. The validity of the explanation must itself be examined. _Four Decades of Scientific Explanation_ provides a comprehensive account of the developments in scientific explanation that transpired in the last four decades of the twentieth century. It continues to stand as the most comprehensive treatment of the writings on the subject during these years. Building on the historic 1948 essay (...) by Carl G. Hempel and Paul Oppenheim, "Studies in the Logic of Explanation,” which introduced the deductive-nomological model on which most work on scientific explanation was based for the following four decades, Salmon goes beyond this model's inherent basis of describing empirical knowledge to tells us “not only _what,_ but also _why_.” Salmon examines the predominant models in chronological order and describes their development, refinement, and criticism or rejection. _Four Decades of Scientific Explanation_ underscores the need for a consensus of approach and ongoing evaluations of methodology in scientific explanation, with the goal of providing a better understanding of natural phenomena. (shrink)

In a now classic paper published in 1991, Alberch introduced the concept of genotype–phenotype (G!P) mapping to provide a framework for a more sophisticated discussion of the integration between genetics and developmental biology that was then available. The advent of evo-devo first and of the genomic era later would seem to have superseded talk of transitions in phenotypic space and the like, central to Alberch’s approach. On the contrary, this paper shows that recent empirical and theoretical advances have only sharpened (...) the need for a different conceptual treat- ment of how phenotypes are produced. Old-fashioned metaphors like genetic blueprint and genetic programme are not only woefully inadequate but positively misleading about the nature of G!P, and are being replaced by an algorithmic approach emerging from the study of a variety of actual G!P maps. These include RNA folding, protein function and the study of evolvable soft- ware. Some generalities are emerging from these disparate fields of analysis, and I suggest that the concept of ‘developmental encoding’ (as opposed to the classical one of genetic encoding) provides a promising computational–theoretical underpinning to coherently integrate ideas on evolvability, modularity and robustness and foster a fruitful framing of the G!P mapping problem. (shrink)

Evolutionary theory is undergoing an intense period of discussion and reevaluation. This, contrary to the misleading claims of creationists and other pseudoscientists, is no harbinger of a crisis but rather the opposite: the field is expanding dramatically in terms of both empirical discoveries and new ideas. In this essay I briefly trace the conceptual history of evolutionary theory from Darwinism to neo-Darwinism, and from the Modern Synthesis to what I refer to as the Extended Synthesis, a more inclusive conceptual framework (...) containing among others evo–devo, an expanded theory of heredity, elements of complexity theory, ideas about evolvability, and a reevaluation of levels of selection. I argue that evolutionary biology has never seen a paradigm shift, in the philosophical sense of the term, except when it moved from natural theology to empirical science in the middle of the 19th century. The Extended Synthesis, accordingly, is an expansion of the Modern Synthesis of the 1930s and 1940s, and one that—like its predecessor—will probably take decades to complete. (shrink)

The formal framework of Kauffman (1991) depicts the constraints of self-organization on the evolution of complex systems and the relation of self-organization to selection. We discuss his treatment of 'generic constraints' as sources of order (section 2) and the relation between adaptation and organization (section 3). We then raise a number of issues, including the role of adaptation in explaining order (section 4) and the limitations of formal approaches in explaining the distinctively biological (section 5). The principal question we pose (...) is the relation of generic constraints on evolution to more specific local constraints, imposed, for example, by the characteristic materials out of which organisms are constructed, the accidental features characteristic of the Bauplan of a lineage, and the local vicissitudes of adaptation. We offer no answer to this large question. (shrink)