ArticleMolecular biology and evolution2025
Structural Changes in Gene Ontology Reveal Modular and Complex Representations of Biological Function.
Article in Molecular biology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- The Constrained Disorder Principle: A Paradigm Shift for Accurate Interactome Mapping and Information Analysis in Complex Biological Systems.Bioengineering (Basel, Switzerland) · 2025Review
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Authors and funding
8 authors.
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Abstract
The Gene Ontology is a central resource for representing biological knowledge, yet its internal structure is often treated as static-or as a black box-in computational analyses. Here, we examine 15 years of Gene Ontology evolution using network-based methods, revealing that Gene Ontology changes not only through incremental growth but also through punctuated, curator-driven restructuring. In particular, we document a major reorganization of the Cellular Component branch in 2019, where broad "part" terms were removed and the ontology was modularized into distinct domains for anatomical entities and protein-containing complexes. Semantic modularity aligns Gene Ontology with emerging frameworks such as the Common Anatomy Reference Ontology and Gene Ontology-Causal Activity Modeling, but also disrupts similarity metrics that rely solely on hierarchical proximity. More broadly, the restructuring of the cellular components branch consolidates a shift toward treating Gene Ontology as a multi-layer semantic network-a transformation rooted in a decade-long process of scientific and social consensus across institutions. These findings underscore the need for version-aware, multi-layer models to ensure reproducibility and interpretability-and to better represent biological function across compositional, spatial, and regulatory dimensions as ontologies continue to evolve.
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