This thesis addresses philosophical issues regarding the young field of systems biology. Systems biologists commonly present their approach as a superior alternative to ‘traditional’ molecular biology that they describe as being overly ‘reductionist.’ However, the heterogeneity of systems approaches makes it difficult to understand what ‘the’ approach of systems biology exactly consists in. Here I propose a framework for the systematic comparison of different scientific approaches in biology. I argue that the relevant issues arise at the level of strategies of mechanistic discovery. These strategies are best understood as ‘heuristic,’ that is, as tools to reduce the complexity of a given research task. While having the virtue of making the search for mechanisms more efficient, heuristic strategies rely on particular assumptions about the system under study. This can introduce bias and lead biologists to underestimate the actual complexity of the system. Framing the analysis in terms of heuristic strategies pro- vides a precise way to distinguish between different approaches and to better understand the ongoing rhetoric battles. I discuss a number of case studies, both from molecular biology and from systems biology. I argue that the traditional approach of molecular biology relies on a relatively well-defined set of heuristics that corresponds to a particular idea of the organization and complexity of living systems. Approaches in systems biology relax some of the underlying assumptions of the traditional approach, notably by applying tools of mathematical modeling, but they have to make use of alternative heuristics in order to be efficient. As a result, they rely on different assumptions about organization and complexity. My detailed discussion of case studies reveals that there are a number of different systems approaches that can be distinguished by analyzing their heuristic character. The ambition of systems biologists to build formal models of biological mechanisms, however, has the virtue of making many of the underlying assumptions explicit which helps to recognize and reduce bias, and moreover facilitates the integration of different approaches. Some of the issues touched upon also have relevance for more general questions in the philosophy of biology. Assumptions about biological organization and complexity can heavily influence what we think of as a good scientific explanation. Since systems biology puts into question some of these assumptions, we might be forced to revise our ideas about mechanistic explanation. I argue that notably the concept of biological robustness has to be taken into account by philosophers who are thinking about mechanisms in biology.

THE SUM OF THE PARTS: HEURISTIC STRATEGIES IN SYSTEMS BIOLOGY / F. Gross ; supervisore: M. Bedau; supervisore interno: A. Ciliberto; supervisore esterno: W. Wimsatt. UNIVERSITA' DEGLI STUDI DI MILANO, 2013 Mar 04. 24. ciclo, Anno Accademico 2012. [10.13130/gross-fridolin_phd2013-03-04].

THE SUM OF THE PARTS: HEURISTIC STRATEGIES IN SYSTEMS BIOLOGY

F. Gross
2013

Abstract

This thesis addresses philosophical issues regarding the young field of systems biology. Systems biologists commonly present their approach as a superior alternative to ‘traditional’ molecular biology that they describe as being overly ‘reductionist.’ However, the heterogeneity of systems approaches makes it difficult to understand what ‘the’ approach of systems biology exactly consists in. Here I propose a framework for the systematic comparison of different scientific approaches in biology. I argue that the relevant issues arise at the level of strategies of mechanistic discovery. These strategies are best understood as ‘heuristic,’ that is, as tools to reduce the complexity of a given research task. While having the virtue of making the search for mechanisms more efficient, heuristic strategies rely on particular assumptions about the system under study. This can introduce bias and lead biologists to underestimate the actual complexity of the system. Framing the analysis in terms of heuristic strategies pro- vides a precise way to distinguish between different approaches and to better understand the ongoing rhetoric battles. I discuss a number of case studies, both from molecular biology and from systems biology. I argue that the traditional approach of molecular biology relies on a relatively well-defined set of heuristics that corresponds to a particular idea of the organization and complexity of living systems. Approaches in systems biology relax some of the underlying assumptions of the traditional approach, notably by applying tools of mathematical modeling, but they have to make use of alternative heuristics in order to be efficient. As a result, they rely on different assumptions about organization and complexity. My detailed discussion of case studies reveals that there are a number of different systems approaches that can be distinguished by analyzing their heuristic character. The ambition of systems biologists to build formal models of biological mechanisms, however, has the virtue of making many of the underlying assumptions explicit which helps to recognize and reduce bias, and moreover facilitates the integration of different approaches. Some of the issues touched upon also have relevance for more general questions in the philosophy of biology. Assumptions about biological organization and complexity can heavily influence what we think of as a good scientific explanation. Since systems biology puts into question some of these assumptions, we might be forced to revise our ideas about mechanistic explanation. I argue that notably the concept of biological robustness has to be taken into account by philosophers who are thinking about mechanisms in biology.
4-mar-2013
Settore M-FIL/02 - Logica e Filosofia della Scienza
systems biology ; scientific discovery ; mechanistic explanation ; heuristics
BEDAU, MARK
Doctoral Thesis
THE SUM OF THE PARTS: HEURISTIC STRATEGIES IN SYSTEMS BIOLOGY / F. Gross ; supervisore: M. Bedau; supervisore interno: A. Ciliberto; supervisore esterno: W. Wimsatt. UNIVERSITA' DEGLI STUDI DI MILANO, 2013 Mar 04. 24. ciclo, Anno Accademico 2012. [10.13130/gross-fridolin_phd2013-03-04].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/218890
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