Robert Richardson

Mechanistic models in molecular systems biology are generally mathematical models of the action of networks of biochemical reactions, involving metabolism, signal transduction, and/or gene expression. They can be either simulated numerically or analyzed analytically. Systems biology integrates quantitative molecular data acquisition with mathematical models to design new experiments, discriminate between alternative mechanisms and explain the molecular basis of cellular properties. At the heart of this approach are mechanistic models of molecular networks. We focus on the articulation and development of mechanistic models, identifying five constraints which guide the articulation of models in molecular systems biology. These constraints are not independent of one another, with the result that modeling becomes an iterative process. We illustrate the use of these constraints in the modeling of the mechanism for bistability in the lac operon.

Optimization models treat natural selection as a process tending to produce maximal adaptedness to the environment, measured on some "criterion scale" defining the optimal phenotype. These models are descriptively adequate if they describe the outcomes of evolutionary processes. They are dynamically adequate if the variables which describe the outcomes also are responsible for those evolutionary outcomes. Optimality models can be descriptively adequate, but dynamically unrealistic. Relying on cases from evolutionary ecology, I provide reasons to question the dynamic adequacy of optimality models, and offer reasons for distinguishing, at least at a theoretical level, between satisficing and optimizing.

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.

Developmental biology has resurfaced in recent years, often without a clearly central role for the organism. The organism is pulled in divergent directions: on the one hand, there is an important body of work that emphasizes the role of the gene in development, as executing and controlling embryological change; on the other hand, there are more theoretical approaches under which the organism disappears as little more than an instance for testing biological generalizations. I press here for the ineliminability of the organism in developmental biology on explanatory grounds. I examine classical work concerned with growth and development, particularly in Drosophila and C. elegans. Some of this work is suggestive of modular development, and accordingly suggests a level below that of the organism as being explanatory. These are not the only type of case. There are other equally well-established results, which indicate greater integration in the developing organism. Though with a modular organization the organism can be thought of as made up of its constituent traits, and though the explanations of these traits may lie in terms of cells or genes, even with modular development the explanations of "genetic" differences require an appeal to the organism. With non-modular organization the organism has an even more central role. This does not mean that these genetic or cellular contributions are unreal in any way, or that development requires some sort of vitalistic contribution; but the genetic contributions make sense only as constituents of the organism, embedded in a larger organic context

Evolutionary models can explain the dynamics of populations, how genetic, genotypic, or phenotypic frequencies change with time. Models incorporating chance, or drift, predict specific patterns of change. These are illustrated using classic work on blood types by Cavalli-Sforza and his collaborators in the Parma Valley of Italy, in which the theoretically predicted patterns are exhibited in human populations. These data and the models display properties of ensembles of populations. The explanatory problem needs to be understood in terms of how likely an observed change, in either a population or an ensemble, would be under drift alone; this is fundamentally a matter of chance. Understood in this way, issues of drift and chance undercut most recent philosophical, but not biological, discussions of the role of "genetic drift.".

  Pickering and Chater (P&C) maintain that folk psychology and cognitive science should neither compete nor cooperate. Each is an independent enterprise, with a distinct subject matter and characteristic modes of explanation. P&C''s case depends upon their characterizations of cognitive science and folk psychology. We question the basis for their characterizations, challenge both the coherence and the individual adequacy of their contrasts between the two, and show that they waver in their views about the scope of each. We conclude that P&C do not so muchdiscover ascreate the gap they find between folk psychology and cognitive science. It is an artifact of their implausible and unmotivated attempt to demarcate the two areas, and of the excessively narrow accounts they give of each

  Evolutionary psychology purports to explain human capacities as adaptations to an ancestral environment. A complete explanation of human language or human reasoning as adaptations depends on assessing an historical claim, that these capacities evolved under the pressure of natural selection and are prevalent because they provided systematic advantages to our ancestors. An outline of the character of the information needed in order to offer complete adaptation explanations is drawn from Robert Brandon (1990), and explanations offered for the evolution of language and reasoning within evolutionary psychology are evaluated. Pinker and Bloom's (1992) defense of human language as an adaptation for verbal communication, Robert Nozick's (1993) account of the evolutionary origin of rationality, and Cosmides and Tooby's (1992) explanation of human reasoning as an adaptation for social exchange, are discussed in light of what is known, and what is not known, about the history of human evolution. In each case, though a plausible case is made that these capacities are adaptations, there is not enough known to offer even a semblance of an explanation of the origin of these capacities. These explanations of the origin of human thought and language are simply speculations lacking the kind of detailed historical information required for an evolutionary explanation of an adaptation