Systems Biology and Education

Philosophy of Systems Biology

2016

The intention with this volume is to provide a format for scholars to express their personal viewpoints and tell their story in response to the same set of questions (see Preface). Unlike many edited volumes, this book is therefore not divided into thematic sections. The aim of this introduction is to summarize core common themes among the contributor's chapters so as to guide readers interested in specific topics. Given the richness of the contributions that touch upon many diverse topics in response to the posed questions, I have not summarized each contribution separately. Rather, I focus on core questions and highlight where more information on common themes and novel insights can be found. I also hope that the introduction will provide some background for scientists, philosophers as well as other readers interested in discussing the philosophical implications of systems biology. What is systems biology?Broadly understood, systems biology aims to capture the dynamic complexity of living systems through the combination of mathematical, computational and experimental strategies (Kitano 2001). One overarching research question is how biological function emerges from the interactions of processes whose dynamics are nonlinear and constrained by the organization of the system as a whole (cf. Wolkenhauer, Chapter 24). Research in systems biology is driven by complex problems requiring interdisciplinary solutions, but there are different views on the most significant methods, values and aims of systems biology. Some scholars emphasize computational integration of big data from multiple sources as a characteristic feature of systems biology (Aderem 2005), whereas others stress that systems biology is a merger of systems theory with biology (Wolkenhauer and Mesarović 2005). Differences in theoretical and methodological standpoints are sometimes characterized by the differences between pragmatic and systems-theoretical systems biology: the former sees systems biology as a straightforward extension of genomics and molecular biology and the latter highlights the need for a formal systems theory of living systems (O'Malley and Dupré, 2005, for further reflections see Boogerd et al. 2007). In both cases, however, researchers must navigate in what Nersessian (Chapter 20) calls an adaptive problem space where knowledge and methods are continuously reconfigured and combined into new hybrid methods, concepts, and models. The combination of theoretical reflection and technologically mediated methodological innovations make systems biology particularly intriguing from a philosophical perspective.It is debatable whether systems biology brings something radically new to the life sciences. Systems biology has been described in terms as different as a new 'holistic paradigm' or 'revolution' in biology to being merely a 'buzzword' used for funding purposes (Kastenhofer 2013b). It is difficult to point to radical historical shifts or 'revolutions', but systems biology develops in a unique historical and technological context offering ...

Section: Explanations and Design Principlesmentioning

confidence: 99%

Section: Explanations and Design Principlesmentioning

confidence: 99%

Section: Explanations and Design Principlesmentioning

confidence: 99%

See 1 more Smart Citation

Introduction to Philosophy of Systems Biology

Philosophy of Systems Biology

2016

“…The goal is to identify organizational patterns that may otherwise be lost in the preoccupation with molecular details. If the same principles can be applied in the design of different types of engineered systems from cars to computers or airplanes, it seems likely that some principles are shared among different biological systems or even among engineered and biological systems (Braillard, 2010). The objective to identify shared formal criteria for functional design is not new.…”

Section: The Virtues and Pitfalls Of Reverse Engineeringmentioning

confidence: 99%

“…Contrary to what one would expect from Braun and Marom's (this issue) account, a key insight provided by reverse engineering analyses is that robustness is often not attained through fine-tuning of specific mechanisms but due to features associated with the organization of the system. Architectural features of robust systems have been demonstrated for robustness to gradients in embryonic patterning (Eldar et al, 2002), concentration robustness in biochemical reaction networks (Shinar and Feinberg, 2011), for bacterial chemotaxis (reviewed in Braillard, 2010), and for the spindle assembly checkpoint mechanism in cell division (reviewed in Gross, 2013). Thus, engineering-inspired research in systems biology is directly related to the aim of understanding what robust networks have in common in terms of system-level organizational features, and to identify organizational features that may or may not work for a given property.…”

Section: Final Version Published In Studies In History and Philosophymentioning

confidence: 99%

Can biological complexity be reverse engineered?

Studies in History and Philosophy of Science Part C: Studies in

2015

Concerns with the use of engineering approaches in biology have recently been raised. I examine two related challenges to biological research that I call the synchronic and diachronic underdetermination problem. The former refers to challenges associated with the inference of design principles underlying system capacities when the synchronic relations between lowerlevel processes and higher-level systems capacities are degenerate (many-to-many). The diachronic underdetermination problem regards the problem of reverse engineering a system when the non-linear relations between system capacities and lower-level mechanisms are changing over time. Braun and Marom argue that recent insights to biological complexity leave the aim of reverse engineering hopeless -in principle as well as in practice. While I support their call for systemic approaches to capture the dynamic nature of living systems, I take issue with the conflation of reverse engineering with naïve reductionism. I clarify how the notion of design principles can be more broadly conceived and argue that reverse engineering is compatible with a dynamic view of organisms. It may even help to facilitate an integrated account that bridges the gap between mechanistic and systems approaches.Keywords: Reverse engineering, design principles, diachronic underdetermination, systems biology, engineering approaches, dynamical systems theory The virtues and pitfalls of reverse engineeringReverse engineering methodologies are currently gaining terrain in biological fields such as systems biology and neuroscience. In response to these developments, experimental biologists have raised concerns regarding the associated quest for design principles that they take to imply an assumption of a rather static and modular design of organisms. A workshop in Konstanz brought together philosophers and biologists to discuss the implications of research methodologies in the life sciences. 2 This paper focuses in particular on concerns raised regarding reverse engineering of biological networks.The experimental biologists Erez Braun and Shimon Marom (this issue) provide fascinating insights to biological complexity by stressing how living systems are characterized by a (deep) two-way degeneracy and lack of separation of time-scales. Against this complexity, they criticize so-called reverse engineering approaches for investigating biological systems as if these were programmed and fully decomposable engineering systems, designed to conduct pre-designed functions. This paper clarifies and supports their criticism of naïve

Systems science and the art of interdisciplinary integration

Andersen

2019

Syst Res Behav Sci

Systems sciences address issues that cross‐cut any single discipline and benefit from the synergy of combining several approaches. But interdisciplinary integration can be challenging to achieve in practice. Scientists with different disciplinary backgrounds often have different views on what count as good data, good evidence, a good model, or a good explanation. Accordingly, several scholars have reported on challenges encountered in interdisciplinary settings. This chapter outlines how some of the challenges play out in systems biology where disciplinary ideals and domainspecific practices sometime collide. We focus on tensions arising due to differences in epistemic standards between modellers with a background in physics or systems engineering, on one hand, and experimenters with a background in molecular biology on the other. We propose that part of the problem of interdisciplinary integration can be understood as the result of unfounded “disciplinary imperialism” on both sides, in which standards from one discipline are uncritically applied to new domains without recognition of other valid or complementary perspectives. Addressing and explicating the disciplinary background for the different views can help facilitate interdisciplinary collaboration in science and improve science education.