ArticleSynthese2018
Mechanistic and topological explanations in medicine: the case of medical genetics and network medicine.
Article in Synthese, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- TargetPrior: a miRNA-signature embedded evolutionary learning framework for prioritizing drug targets in acute myeloid leukemia.Bioinformatics (Oxford, England) · 2026Article
- Functional brain connectivity in patients withNeuroimage. Reports · 2026Article
- Biological detail and graph structure in network neuroscience.Frontiers in network physiology · 2025Review
- Approaches in Post-Experimental Science. The Case of Precision Medicine.Berichte zur Wissenschaftsgeschichte · 2022Article
- Using network models in person-centered care in psychiatry: How perspectivism could help to draw boundaries.Frontiers in psychiatry · 2022Review
- Integrating Philosophy of Understanding With the Cognitive Sciences.Frontiers in systems neuroscience · 2022Article
- Are topological explanations really free of mechanisms?Theory in biosciences = Theorie in den Biowissenschaften · 2021Article
- General theory of topological explanations and explanatory asymmetry.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020Article
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Abstract
Medical explanations have often been thought on the model of biological ones and are frequently defined as mechanistic explanations of a biological dysfunction. In this paper, I argue that topological explanations, which have been described in ecology or in cognitive sciences, can also be found in medicine and I discuss the relationships between mechanistic and topological explanations in medicine, through the example of network medicine and medical genetics. Network medicine is a recent discipline that relies on the analysis of various disease networks (including disease-gene networks) in order to find organizing principles in disease explanation. My aim is to show how topological explanations in network medicine can help solving the conceptual issues that pure mechanistic explanations of the genetics of disease are currently facing, namely the crisis of the concept of genetic disease, the progressive geneticization of diseases and the dissolution of the distinction between monogenic and polygenic diseases. However, I will also argue that topological explanations should not be considered as independent and radically different from mechanistic explanations for at least two reasons. First, in network medicine, topological explanations depend on and use mechanistic information. Second, they leave out some missing gaps in disease explanation that require, in turn, the development of new mechanistic explanations. Finally, I will insist on the specific contribution of topological explanations in medicine: they push us to develop an explanation of disease in general, instead of focusing on single explanations of individual diseases. This last point may have major consequences for biomedical research.
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