ArticleHistory and philosophy of the life sciences2018
Modeling complexity: cognitive constraints and computational model-building in integrative systems biology.
Article in History and philosophy of the life sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- From prior knowledge to data-informed models: a review of Boolean network inference.Briefings in bioinformatics · 2026Review
- Striking the balance: Complexity, simplicity, and credibility in mathematical biology.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- An adaptableMolecular omics · 2024Article
- Causation in neuroscience: keeping mechanism meaningful.Nature reviews. Neuroscience · 2024Review
- Modeling preferential attraction to infected hosts in vector-borne diseases.Frontiers in public health · 2023Article
- The Future of Burn Care From a Complexity Science Perspective.Journal of burn care & research : official publication of the American Burn Association · 2022Article
- Gluing life together. Computer simulation in the life sciences: an introduction.History and philosophy of the life sciences · 2018Article
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Authors and funding
2 authors.
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Abstract
Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other tools to handle the cognitive complexity of their modeling problems so as to be able to make significant contributions to understanding, intervening in, and controlling complex biological systems. We thus show how cognition, especially processes of simulative mental modeling, is implicated centrally in processes of model-building. At the same time we suggest how the representational choices of what to model in systems biology are limited or constrained as a result. Such constraints help us both understand and rationalize the restricted form that problem solving takes in the field and why its results do not always measure up to expectations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.