Big data biology—bioinformatics, computational biology, systems biology (including ‘omics’), and synthetic biology—raises a number of issues for the philosophy of science. This article deals with several such: Is data-intensive biology a new kind of science, presumably post-reductionistic? To what extent is big data biology data-driven? Can data ‘speak for themselves?’ I discuss these issues by way of a reflection on Carl Woese’s worry that “a society that permits biology to become an engineering discipline, that allows that science to slip into (...) the role of changing the living world without trying to understand it, is a danger to itself.” And I argue that scientific perspectivism, a philosophical stance represented prominently by Giere, Van Fraassen, and Wimsatt, according to which science cannot as a matter of principle transcend our human perspective, provides the best resources currently at our disposal to tackle many of the philosophical issues implied in the modeling of complex, multilevel/multiscale phenomena. (shrink)

The relationship between machine learning and the philosophy of science can be classed as a dynamic interaction: a mutually beneficial connection between two autonomous fields that changes direction over time. I discuss the nature of this interaction and give a case study highlighting interactions between research on Bayesian networks in machine learning and research on causality and probability in the philosophy of science.

The discovery and ongoing investigation of microRNAs suggest important conceptual and methodological lessons for philosophers and historians of biology. This paper provides an account of miRNA research and the shift from viewing these tiny regulatory entities as minor curiosities to seeing them as major players in the post-transcriptional regulation of genes. Conceptually, the study of miRNAs is part of a broader change in understandings of genetic regulation, in which simple switch-like mechanisms were reinterpreted as aspects of complex cellular and genome-wide (...) processes. Among them are the activities of small RNAs, previously regarded as non-functional. Methodologically, the miRNA story suggests new ways of characterizing biological research that should prove helpful to philosophers of science who seek to develop more pluralistic, pragmatic models of scientific inquiry. miRNA research displays iterative movements between multiple modes of investigation that include not only the proposal and testing of hypotheses but also exploratory, technology-oriented and question-driven modes of research. As an exemplary story of scientific discovery and development, the miRNA case illustrates transitions from genetics to genomics and systems biology, and it shows how diverse configurations of research practice are related to major scientific advances. (shrink)

In the context of scientists' reflections on genomics, we examine some fundamental issues in the emerging postgenomic discipline of systems biology. Systems biology is best understood as consisting of two streams. One, which we shall call ‘pragmatic systems biology’, emphasises large‐scale molecular interactions; the other, which we shall refer to as ‘systems‐theoretic biology’, emphasises system principles. Both are committed to mathematical modelling, and both lack a clear account of what biological systems are. We discuss the underlying issues in identifying systems (...) and how causality operates at different levels of organisation. We suggest that resolving such basic problems is a key task for successful systems biology, and that philosophers could contribute to its realisation. We conclude with an argument for more sociologically informed collaboration between scientists and philosophers. BioEssays 27:1270–1276, 2005. © 2005 Wiley Periodicals, Inc. (shrink)

Knowledge-making practices in biology are being strongly affected by the availability of data on an unprecedented scale, the insistence on systemic approaches and growing reliance on bioinformatics and digital infrastructures. What role does theory play within data-intensive science, and what does that tell us about scientific theories in general? To answer these questions, I focus on Open Biomedical Ontologies, digital classification tools that have become crucial to sharing results across research contexts in the biological and biomedical sciences, and argue that (...) they constitute an example of classificatory theory. This form of theorizing emerges from classification practices in conjunction with experimental know-how and expresses the knowledge underpinning the analysis and interpretation of data disseminated online. (shrink)

It is considered in some quarters that hypothesis‐driven methods are the only valuable, reliable or significant means of scientific advance. Data‐driven or ‘inductive’ advances in scientific knowledge are then seen as marginal, irrelevant, insecure or wrong‐headed, while the development of technology—which is not of itself ‘hypothesis‐led’ (beyond the recognition that such tools might be of value)—must be seen as equally irrelevant to the hypothetico‐deductive scientific agenda. We argue here that data‐ and technology‐driven programmes are not alternatives to hypothesis‐led studies in (...) scientific knowledge discovery but are complementary and iterative partners with them. Many fields are data‐rich but hypothesis‐poor. Here, computational methods of data analysis, which may be automated, provide the means of generating novel hypotheses, especially in the post‐genomic era. BioEssays 26:99–105, 2004. © 2003 Wiley Periodicals, Inc. (shrink)

This paper offers a contribution to debates around integrative aspects of systems biology and engages with issues related to the circumstances under which physicists look at biological problems. We use oral history as one of the methodological tools to gather the empirical material, conducting interviews with physicists working in systems biology. The interviews were conducted at several institutions in Brazil, Germany, Israel and the U.S. Biological research has been increasingly dependent on computational methods, high-throughput technologies, and multidisciplinary skills. Quantitative scientists (...) are joining biological departments and collaborations between physicists and biologists are particularly vigorous. This state of affairs raises a number of questions, such as: What are the circumstances under which physicists approach biological problems in systems biology? What kind of interdisciplinary challenges must be tackled? The paper suggests that, concerning physicists’ move to work on biological systems, there are common reasons to move, the transition must be understood in terms of degrees, physicists have a rationale for simplifying systems, and distinct conceptions of model and modeling strategies are recurrent. We identified problems regarding linguistic clarity and integration of epistemological aims. We conclude that cultural unconformities within the systems biology community have important consequences to the flow of scientific knowledge. (shrink)

This paper offers a contribution to debates around integrative aspects of systems biology and engages with issues related to the circumstances under which physicists look at biological problems. We use oral history as one of the methodological tools to gather the empirical material, conducting interviews with physicists working in systems biology. The interviews were conducted at several institutions in Brazil, Germany, Israel and the U.S. Biological research has been increasingly dependent on computational methods, high-throughput technologies, and multidisciplinary skills. Quantitative scientists (...) are joining biological departments and collaborations between physicists and biologists are particularly vigorous. This state of affairs raises a number of questions, such as: What are the circumstances under which physicists approach biological problems in systems biology? What kind of interdisciplinary challenges must be tackled? The paper suggests that, concerning physicists’ move to work on biological systems, there are common reasons to move, the transition must be understood in terms of degrees, physicists have a rationale for simplifying systems, and distinct conceptions of model and modeling strategies are recurrent. We identified problems regarding linguistic clarity and integration of epistemological aims. We conclude that cultural unconformities within the systems biology community have important consequences to the flow of scientific knowledge. (shrink)

This paper offers a contribution to debates around integrative aspects of systems biology and engages with issues related to the circumstances under which physicists look at biological problems. We use oral history as one of the methodological tools to gather the empirical material, conducting interviews with physicists working in systems biology. The interviews were conducted at several institutions in Brazil, Germany, Israel and the U.S. Biological research has been increasingly dependent on computational methods, high-throughput technologies, and multidisciplinary skills. Quantitative scientists (...) are joining biological departments and collaborations between physicists and biologists are particularly vigorous. This state of affairs raises a number of questions, such as: What are the circumstances under which physicists approach biological problems in systems biology? What kind of interdisciplinary challenges must be tackled? The paper suggests that, concerning physicists’ move to work on biological systems, there are common reasons to move, the transition must be understood in terms of degrees, physicists have a rationale for simplifying systems, and distinct conceptions of model and modeling strategies are recurrent. We identified problems regarding linguistic clarity and integration of epistemological aims. We conclude that cultural unconformities within the systems biology community have important consequences to the flow of scientific knowledge. (shrink)

The biological sciences study (bio)complex living systems. Research directed at the mechanistic explanation of the "live" state truly requires a pluralist research program, i.e. BioComplexity research. The program should apply multiple intra-level and inter-level theories and methodologies. We substantiate this thesis with analysis of BioComplexity: metabolic and modular control analysis of metabolic pathways, emergence of oscillations, and the analysis of the functioning of glycolysis.

This paper is devoted to an examination of the discovery, characterization, and analysis of the functions of microRNAs, which also serves as a vehicle for demonstrating the importance of exploratory experimentation in current (post-genomic) molecular biology. The material on microRNAs is important in its own right: it provides important insight into the extreme complexity of regulatory networks involving components made of DNA, RNA, and protein. These networks play a central role in regulating development of multicellular organisms and illustrate the importance (...) of epigenetic as well as genetic systems in evolution and development. The examination of these matters yields principled arguments for the historicity of the functions of key biological molecules and for the indispensability of exploratory experimentation in contemporary molecular biology as well as some insight into the complex interplay between exploratory experimentation and hypothesis-driven science. This latter result is not only important for philosophy of science, but also of practical importance for the evaluation of grant proposals, although the elaboration of this latter claim must be left for another occasion. (shrink)