ArticleSystems and synthetic biology2013
An attempt to construct a (general) mathematical framework to model biological "context-dependence".
Article in Systems and synthetic biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- CENTRA: knowledge-based gene contextuality graphs reveal functional master regulators by centrality and fractality.NAR genomics and bioinformatics · 2025Article
- Exploring the differences in metabolic behavior of astrocyte and glioblastoma: a flux balance analysis approach.Systems and synthetic biology · 2015Article
- Computational model for monitoring cholesterol metabolism.Systems and synthetic biology · 2014Article
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Authors and funding
1 author.
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Abstract
Context-dependent nature of biological phenomena is well documented in every branch of biology. While there have been few previous attempts to (implicitly) model various (particular) facets of biological context-dependence, a formal and general mathematical construct to model the wide spectrum of context-dependence, eludes the students of biology. Such an objective model, from both 'bottom-up' as well as 'top-down' perspective, is proposed here to serve as the template to describe the various kinds of context-dependence that we encounter in different branches of biology. Interactions between biological contexts was found to be transitive but non-commutative. It is found that a hierarchical nature of dependence among the biological contexts models the emergent biological properties efficiently. Reasons for these findings are provided in a general model to describe biological reality. Scheme to algorithmically implement the hierarchic structure of organization of biological contexts was proposed with a construct named 'Context tree'. A 'Context tree' based analysis of context interactions among biophysical factors influencing protein structure was performed.
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