In describing the flawless regularity of developmental processes and the correlation between changes at certain genetic loci and changes in morphology, biologists frequently employ two metaphors: that genes ‘control’ development, and that genomes embody ‘programs’ for development. Although these metaphors have an admirable sharpness and punch, they lead, when taken literally, to highly distorted pictures of developmental processes. A more balanced, and useful, view of the role of genes in development is that they act as suppliers of the material needs (...) of development and, in some instances, as context‐dependent catalysts of cellular changes, rather than as ‘controllers’ of developmental progress and direction. The consequences of adopting this alternative view of development are discussed. (shrink)

Published research findings are sometimes refuted by subsequent evidence, says Ioannidis, with ensuing confusion and disappointment.

We will show that there is a strong form of emergence in cell biology. Beginning with C.D. Broad’s classic discussion of emergence, we distinguish two conditions sufficient for emergence. Emergence in biology must be compatible with the thought that all explanations of systemic properties are mechanistic explanations and with their sufficiency. Explanations of systemic properties are always in terms of the properties of the parts within the system. Nonetheless, systemic properties can still be emergent. If the properties of the components (...) within the system cannot be predicted, even in principle, from the behavior of the system’s parts within simpler wholes then there also will be systemic properties which cannot be predicted, even in principle, on basis of the behavior of these parts. We show in an explicit case study drawn from molecular cell physiology that biochemical networks display this kind of emergence, even though they deploy only mechanistic explanations. This illustrates emergence and its place in nature. (shrink)

We will show that there is a strong form of emergence in cell biology. Beginning with C.D. Broad's classic discussion of emergence, we distinguish two conditions sufficient for emergence. Emergence in biology must be compatible with the thought that all explanations of systemic properties are mechanistic explanations and with their sufficiency. Explanations of systemic properties are always in terms of the properties of the parts within the system. Nonetheless, systemic properties can still be emergent. If the properties of the components (...) within the system cannot be predicted, even in principle, from the behavior of the system's parts within simpler wholes then there also will be systemic properties which cannot be predicted, even in principle, on basis of the behavior of these parts. We show in an explicit case study drawn from molecular cell physiology that biochemical networks display this kind of emergence, even though they deploy only mechanistic explanations. This illustrates emergence and its place in nature. (shrink)

Systems biology is largely tributary to genomics and other “omic” disciplines that generate vast amounts of structural data. “Omics”, however, lack a theoretical framework that would allow using these data sets as such (rather than just tiny bits that are extracted by advanced data-mining techniques) to build explanatory models that help understand physiological processes. Systems biology provides such a framework by adding a dynamic dimension to merely structural “omics”. It makes use of bottom-up and top-down models. The former are based (...) on data about systems components, the latter on systems-level data. We trace back both modeling strategies (which are often used to delineate two branches of the field) to the modeling of metabolic and signaling pathways in the bottom-up case, and to biological cybernetics and systems theory in the top-down case. We then argue that three roots of systems biology must be discerned to account adequately for the structure of the field: pathway modeling, biological cybernetics, and “omics”. We regard systems biology as merging modeling strategies (supplemented by new mathematical procedures) from data-poor fields with data supply from a field that is quite deficient in explanatory modeling. After characterizing the structure of the field, we address some epistemological and ontological issues regarding concepts on which the top-down approach relies and that seem to us to require clarification. This includes the consequences of identifying modules in large networks without relying on functional considerations, the question of the “holism” of systems biology, and the epistemic value of the “systeome” project that aspires to become the cutting edge of the field. (shrink)

In this paper the common association between ontological reductionism and a methodological position called 'Mechanism' is discussed. Three major points are argued for: (1) Mechanism is not to be identified with reductionism in any of its forms; in fact, mechanism leads to a non-reductionist ontology. (2) Biological methodology is thoroughly mechanistic. (3) Mechanism is compatible with at least one form of teleology. Along the way the nature and value of scientific explanations, some recent controversies in biology and why reductionism has (...) proven to be such an attractive position are discussed. (shrink)