Why do we need theories?

Abstract

Theories organize knowledge and construct objectivity by framing observations and experiments. The elaboration of theoretical principles is examined in the light of the rich interactions between physics and mathematics. These two disciplines share common principles of construction of concepts and of the proper objects of inquiry. Theory construction in physics relies on mathematical symmetries that preserve the key invariants observed and proposed by such theory; these invariants buttress the idea that the objects of physics are generic and thus interchangeable and they move along specific trajectories which are uniquely determined, in classical and relativistic physics. In contrast to physics, biology is a historical science that centers on the changes that organisms experience while undergoing ontogenesis and phylogenesis. Biological objects, namely organisms, are not generic but specific; they are individuals. The incessant changes they undergo represent the breaking of symmetries, and thus the opposite of symmetry conservation, a central component of physical theories. This instability corresponds to the changes of the environment and the phenotypes. Inspired by Galileo’s principle of inertia, the “default state” of inert matter, we propose a “default state” for biological dynamics following Darwin’s first principle, “descent with modification” that we transform into “proliferation with variation and motility” as a property that spans life, including cells in an organism. These dissimilarities between theories of the inert and of biology also apply to causality: biological causality is to be understood in relation to the distinctive role that constraints assume in this discipline. Consequently, the notion of cause will be reframed in a context where constraints to activity are seen as the core component of biological analyses. Finally, we assert that the radical materiality of life rules out distinctions such as “software vs. hardware.”

Modeling mammary organogenesis from biological first principles: Cells and their physical constraints

“…Often times, modelers entering biological research treat biological objects as if they were either physical objects or computer programs. In this issue, we have presented critiques to these approaches and suggested biological singularities that have to be taken into consideration when constructing a biological theory (Longo and Soto, 2016; Longo et al, 2015). On the one hand, the metaphorical use of information pushes the experimenter to seek causality in terms of discrete structures, namely molecules, in particular DNA.…”

“…Scientific theories provide organizing principles and construct objectivity by framing observations and experiments (Longo and Soto, 2016). On the one hand, theories construct the proper observables and on the other they provide the framework for studying them.…”

“…Our approach diverges from the biophysical methodology which is based on conservation principles and their associated symmetries, on the one hand, and with optimization principles, on the other. In contrast, biology is about an incessant breaking of symmetries (Longo et al, 2015; Longo and Montévil, 2011; Longo and Soto, 2016). Taking mammary gland morphogenesis as an example, here we show that our theoretical principles are useful to provide a framework for the mathematical modeling of tissue morphogenesis.…”

Over a century of cancer research: Inconvenient truths and promising leads

“…In addition to Boveri's remarks on cancer initiation's observability, other factors have contributed to obfuscation in this field. Namely, since the beginning of the 20th century, leading cell and developmental biologists who once considered theories necessary to understand the objects of inquiry adopted, instead, the belief that reality is directly accessible by the accumulation of data, which made theories superfluous [41][42][43]. Concomitantly, they embraced a reductionist stance [44].…”

Complexity in Biological Organization: Deconstruction (and Subsequent Restating) of Key Concepts

“…In turn, phenomenological modeling of such systems can help in generating and testing hypotheses on such principles [ 2 ]. Complex systems modeling encompasses a different attitude with respect to classical differential equation style adopted for situations in which we can rely on a dee knowledge of basic theoretical principles because of the lack of knowledge of such principles [ 3 ]. Up to now, we can confidently recognize the overwhelming importance of the context in constraining the way the general laws of nature that actively “shape” the specific complexity under scrutiny.…”