Ulrich Krohs

Data without models merging with models without data

SUMMARY 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 the 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

Functions as based on a concept of general design

Looking for an adequate explication of the concept of a biological function, several authors have proposed to link function to design. Unfortunately, known explications of biological design in turn refer to functions. The concept of general design I will introduce here breaks up this circle. I specify design with respect to its ontogenetic role. This allows function to be based on design without making reference to the history of the design, or to the phylogeny of an organism, while retaining the normative aspect of function ascriptions. The concept is applicable to the function and design of technical artifacts as well. Several problems well known with other definitions can be overcome by this approach.

How Digital Computer Simulations Explain Real‐World Processes

Scientists of many disciplines use theoretical models to explain and predict the dynamics of the world. They often have to rely on digital computer simulations to draw predictions fromthe model. But to deliver phenomenologically adequate results, simulations deviate from the assumptions of the theoretical model. Therefore the role of simulations in scientific explanation demands itself an explanation. This paper analyzes the relation between real‐world system, theoretical model, and simulation. It is argued that simulations do not explain processes in the real world directly. The way in which simulations help explaining real‐world processes is conceived as indirect, mediated by the theoretical model. Simulacra are characterized further, and turn out to be a priori measurable. This gives a clue to a better understanding of the epistemic role of computer simulations in scientific research.

Sensitivity of Halobacterium salinarium to attractant light stimuli does not change periodically

Halobacterium salinarium swims alternately in both directions of its cell axis. The average time between two reversals of the swimming direction is modulated by light stimuli. It is a matter of dispute whether the sensitivity to attractant stimuli depends on the time of stimulation during an interval. This question is crucial for model descriptions of the system. I have confirmed constancy of responsiveness with cells adapted to constant conditions and have reconstructed contradicting results. These are shown to be based on inadequate experimental and evaluative methods. The assumption of self‐sustained oscillations which modulate sensitivity can not be justified from the attractant response.

Co-Designing Social Systems by Designing Technical Artifacts: A Conceptual Approach

Technical artifacts are embedded in social systems and, to some extent, even shape them. This chapter inquires, then, whether designing artifacts may be regarded as a contribution to social design. I explicate a concept of general design that conceives design as the type fixation of a complex entity. This allows for an analysis of different contributions to the design of social systems without favoring the intended effects of artifacts on a system over those effects that actually show up. First, the clear-cut case of socio-technical systems is considered. Here, functions of artifacts can be planned fairly precise. In societies, in contrast, the actual functions of an artifact can hardly be predicted, which is due to strong self-organizing processes. Nevertheless artifact design can be shown to contribute to the design of the system also in this case.

The hologenome concept: we need to incorporate function

Are we in the midst of a paradigm change in biology and have animals and plants lost their individuality, i.e., are even so-called ‘typical’ organisms no longer organisms in their own right? Is the study of the holobiont—host plus its symbiotic microorganisms—no longer optional, but rather an obligatory path that must be taken for a comprehensive understanding of the ecology and evolution of the individual components that make up a holobiont? Or are associated microbes merely a component of their host’s environment, and the holobiont concept is just a beautiful idea that does not add much or anything to our understanding of evolution? This article explores different aspects of the concept of the holobiont. We focus on the aspect of functional integration, a central holobiont property, which is only rarely considered thoroughly. We conclude that the holobiont comes in degrees, i.e., we regard the property of being a holobiont as a continuous trait that we term holobiontness, and that holobiontness is differentiated in several dimensions. Although the holobiont represents yet another level of selection (different from classical individual or group selection because it acts on a system that is composed of multiple species), it depends on the grade of functional integration whether or not the holobiont concept helps to cast light on the various degrees of interactions between symbiotic partners.

Epistemic Consequences of Two Different Strategies for Decomposing Biological Networks

It is the mission of systems biology to investigate large biological networks (paradigmatic of cellular extension), and to explain their dynamics by means of mathematical models. Since these networks are far too complex to be modeled directly, they first must be decomposed into subnetworks of mathematically manageable size. This is often done by breaking the network down into quasi-independent modules. Different modularization strategies are applied, relying on functional (physiological) or on structural criteria (related to the topology of the network). This paper demonstrates that choosing a modularization strategy has far-reaching epistemic consequences: The modularization method predefines the kind of model that can be used to describe the network; by this it also predefines the explanatory goals that can be followed successfully. I further challenge the standard view that decomposition of a network according to structural criteria is neutral (while functional decomposition gives a biased picture) and demonstrate that also the choice of a structural criterion introduces a bias.

Overall kinetics of photosystem II: pH dependence and deuterium isotope effect

Abstract The overall kinetics of photosystem II was scanned by means of a double flash technique. Oxygen evolution by pea thylakoids provided with an artificial electron acceptor was measured under a regime of double flashes of variant intervals. The pH optimum in H2O lies near p1H 7.2 (p1H meaning the pH in H2O), with a first-order rate constant of 800 s−1 at 20°C. In deuterium oxide (D2O), a plateau of maximum reaction rate was found between p2H 6.6 and 7.8 (p2H meaning the “pH” in D2O), the highest rate constant being 550 s−1. The apparent kinetic deuterium isotope effect is therefore 1.45. Outside this plateau region, there seems to exist another isotope effect of 1.2 to 1.3. These effects are small but may nevertheless reflect the fact that more than one step of the photosystem II reaction sequence is involved in the splitting of a bond to hydrogen. However, the effects may also be solvent effects or located on the acceptor side of the photosystem.

Semiotic Explanation in the Biological Sciences

Many biological explanations are given in terms of transduced signals and of stored and transferred information. In the following, I call such information-theoretical explanations “semiotic explanations.” Semiotic explanation was hardly ever discussed as a distinct type of explanation. Instead, philosophers looked at information transfer as a somewhat unusual subject of mechanistic explanation and consequently attempted to frame biological information as being observable within physicochemical mechanisms. However, information-theoretical terms never occur in isolation or as a plug-in in mechanistic models but always in the context of information-theoretical models like the semiotic model of protein biosynthesis. This chapter proposes that “information” enters the game as a theoretical term of semiotic models rather than as an observable and that semiotic models have explanatory value by explaining molecular mechanisms in functional rather than in mechanistic terms.

Semiotische Modelle und Theorien

Signalprozesse spielen in biologischen Theorien eine grose Rolle. Da in entsprechenden Modellen mit semiotischer oder informationstheoretischer Terminologie gearbeitet wird, werden die Modelle meist als semiotische Modelle bezeichnet.1 Dieser Terminus soll zunachst nur das in den Modellen verwendete Vokabular charakterisieren, mit ihm sei nichts uber das Auftreten von Zeichen in biologischen Prozessen prasupponiert. Insbesondere wird nicht der Ansatz der Biosemiotik zugrunde gelegt, in dem eine Konzeption des Gebrauchs von Zeichen durch den Organismus und auch durch organische und molekulare Komponenten von Organismen eine zentrale Rolle spielt.2 Die semiotischen Modelle in der Molekularbiologie, alter als die Biosemiotik, sind unabhangig von ihrer Interpretation durch dieses Forschungsprogramm zu betrachten, das keinen Einzug in die molekularbiologische Modellbildung genommen hat.