Research

`En vain nous poussons le vivant dans tel ou tel de nos cadres. Tous les cadres craquent.'
—Henri Bergson, 1907

Research Interests

Areas of Specialisation

Philosophy and History of Biology
General Philosophy of Science
Science and Technology Studies

Topics of Interest

bioinformatics
governance and regulation in genomics
philosophy and history of genomics and system biology
unity and disunity in science
the epistemic role and history of model organisms
the relation between data, phenomena and concepts
social epistemology of biological research communities
role of agency in scientific practice and the communication of knowledge (skills)
political and social dimensions of scientific expertise
elaboration of a research method combining empirical investigation with philosophical analysis of tacit knowledge

Areas of Interest

Early American Pragmatism
Philosophy of the Social Sciences
Political Philosophy (particularly participative democracy and social movements)

Philosophical Issues in Bioinformatics

Theme 1. History and Epistemic Impact of BioOntologies.

My starting point in this project is a philosophical evaluation of the epistemic status of bio-ontologies - that is, the networks of terms used to classify data for dissemination through digital databases. Bio-ontologies aim to enable collaboration across research cultures. Because of this pragmatic motivation, bioinformaticians refer to terms used in bio-ontologies as de facto standards, to be adopted or rejected depending on how helpful they prove towards conducting research on the bench. The characterisation of bio-ontologies as standards does not, however, clarify the implications of choosing specific definitions (to the exclusion of others) to describe the phenomena at hand. Further, it masks their normative role in determining what counts as a research object and in retrieving what is known about it.

I examine the interpretive steps involved in the construction and use of bio-ontologies, and particularly the ways in which concepts are chosen and applied to classify, display and further experimental results (both at the level of gene products and at higher levels of biological organisation).
I examine the epistemic status of experimental results and critically discuss the popular distinction between ‘data-driven’ and ‘hypothesis-driven’ research.
I compare the development and applications of bio-ontologies in the medical and the biological realm, focusing particularly on (1) how bio-ontologies are used to classify human and non-human data (as for instance in the case of the , used to classify data acquired through clinical trials, versus the Gene Ontology, used to classify data from well-established model organisms such as yeast, fruit-flies, thale cress and mice) and (2) how useful bio-ontologies are as taxonomies for Genome Wide Application Studies (GWAS).
I aim to construct a typology of ways in which the idea of ‘knowledge integration’ is interpreted in contemporary bioinformatics and to assess the usefulness of each of these interpretations for biological research. This analysis will contribute to the philosophy of science by exploring how and why classification and standardisation methods, as implemented through new technologies, shape scientific epistemology and foster specific types of knowledge integration.

Theme 2. The Regulatory Role of Bioinformatics

This projects aims to elaborate a sociological and conceptual analysis of the various kinds of governance affecting genomic research and its applications. To this aim, I will examine how various groups within genomics interact to develop bioinformatic tools for the circulation of data, with particular attention to the decision-making processes through which bioinformatic tools are adopted and maintained; their regulatory impact on data circulation; and the implications of adopting these tools for research practices and networks. In particular:

I will focus on the case of the Open Biological Ontologies, and examine how this consortium has established itself as a reference point for the regulation of bio-ontology development. I will also explore the relations between the emergence of bio-ontology consortia and biobanks.
Through semi-structured interviews with database curators working for public and private research structures, I will examine the relation between uses of bio-ontologies within academia and within industry. One important aim of this project is to facilitate constructive dialogue between bioinformaticians working within public and private institutions.
On the basis of the above empirical material, I will discuss the shifting role of scientific expertise in governance, particularly in relation to other types of expertise playing important roles in the regulation of data sharing (as in the case of national and international policy, marketing, diplomacy and public understanding).

Theme 3. The Virtual Plant. How Research on Arabidopsis thaliana Shaped Current Plant Science

This project explores the rise to fame of Arabidopsis thaliana as the most popular model organism in plant biology. How and why did an insignificant plant such as Arabidopsis acquire such prominence? The project answers this question by exploring the history of Arabidopsis use in plant science throughout the 20th century.

I document early attempts to use Arabidopsis as a model for the study of genetic variability across plant ecotypes, and explain the background that led to a sudden global boom in Arabidopsis research in the late 1970s.
I focus particularly on the gradual digitalisation of results coming from Arabidopsis research that took place at the end of the century, and argue that the possibility to store and retrieve these results through the Internet has been a decisive factor in making Arabidopsis into an indispensible research tool.
• I also consider the role of Arabidopsis research in stimulating the development of genetically modified foods and bio-fuels. The digitalisation of Arabidopsis made plant biology eminently applicable within industrial R&D around the world.
Finally, I offer a philosophical reflection on the epistemic role of non-human model organisms. I argue that their prominence in biomedical research is largely due to the inherent ambiguity in their epistemic status: at once sample of nature and man-made artefact, model of other organisms and model for the study of specific hypotheses.

Theme 4. Cross-Species Inference in Model Organism Research

With a focus on taxonomic systems used in human and non-human research and data collecting.

Other Research Interests:

Packaging Small Facts for Travel

When science is in the news, it's usually because of a large finding such as "Smoking Causes Cancer." But such "big facts" are hardly the everyday work of scientists. Instead, researchers are mostly concerned with obtaining and interpreting small facts about the world: measurements, data points, observations. Much of scientists' efforts are directed towards finding strategies and tools to disclose their results and share them with their peers - all in order that they might be used as evidence for the "big facts" we hear so much about. The advancement of science depends on how these small facts are made to travel - but despite the crucial importance of circulating small facts across research contexts, the means and consequences of such travel are not well understood.

Scientific Understanding

My PhD research centred on the notion of scientific understanding: what does it mean to understand `scientifically'? What is the role of theories and models in achieving such understanding? More specifically, how do (1) material practices such as experimentation, modelling and representation and (2) social practices of knowledge exchange inform biologists' understanding of phenomena and thus shape their theories and explanations? I view scientific understanding as an unavoidably pluralistic, individual experience grounded on specific social, intellectual and material circumstances. The notion of understanding is rephrased as the ability to perform specific epistemic activities. Performing activities such as the manipulation of various material as well as conceptual models is crucial to understanding the knowledge derived from the study of the plant. Such modelling activities require specific skills and commitments, which vary depending on the physical features of the models as well as their representational value. Each scientist possesses a different combination of the available/relevant skills and commitments, which determines the quality of his or her understanding. A prominent result of this work concerns the role of tacit knowledge (in the form of performative, conceptual and social skills and associated commitments to specific beliefs and ways of acting) in attaining and exchanging intelligible scientific knowledge. Whether and how a phenomenon is understood depends on the specific experiences, training and perspective of individual researchers. This implies that there are many different ways of understanding natural phenomena: each individual researcher will understand a given phenomenon differently, depending on the conceptual and material tools that she uses, her affiliation with a specific community and her skills and related commitments. My views on these issues are elaborated in my PhD thesis `Weed for Thought. Using Arabidopsis thaliana to Understand Plant Biology'. Click here for a summary and here to download it. Together with Henk de Regt and Kai Eigner, I am in the process of editing a volume titled `Philosophical Perspectives on Scientific Understanding'. More information on this volume and on my contribution to it can be found *somewhere*.

Science And Democracy

Philosophers such as Micheal Polanyi, Thomas Kuhn and Imre lakatos have advocated the so-called internalist position on scientific expertise: the ability to make normative pronouncements on the value and significance of scientific facts can only be acquired within a community whose structure, functioning and goals are geared towards the production of scientific knowledge. This view is motivated by the (correct) observation that scientific claims are produced by skilled individuals, who combine large amounts of specialised theoretical and embodied knowledge to obtain an understanding of the natural world. The conclusion that internalists draw from this observation is that scientists, by virtue of their professional training, are the only class of citizens that is capable of assessing not only the value and significance of scientific results. This conclusion has however been extensively criticised on the basis of a second, equally correct observation: that is, scientists have interests, agendas and priorities that do not always coincide with the interests of other citizens. Thus, it is proposed, the evaluation of scientific claims and their social significance should be open to public scrutiny. What counts as relevant expertise in assessing any scientific claim is the possession of epistemic skills that are relevant to that claim. In particular, scientific understanding of a phenomenon is obtained through the exercise of theoretical and performative skills. Second, epistemic skills are acquired through the experience of interacting with natural phenomena. This means that individuals without a scientific training can also interact with their environment. What counts as relevant epistemic skills varies depending on the type of understanding to be achieved, the interests of the individuals exercising the skills, not only outside of science, but also within scientific research. Take, for instance, current investigations of avian influenza, encompassing its actual and potential distribution and the probability of human contagion. Understanding the features of the virus, and thus deliberating on the implied health risks for humans and other animals, requires skills such as bird-watching and knowledge concerning the behaviour and movements of birds in the wild and in (not entirely industrialised) farms. These skills and knowledge are not acquired through scientific training, but through years of hands-on experience in farming and/or bird-watching — and in fact, scientists investigating avian influenza capitalise on the contribution of farmers and bird-watchers to their investigations.