ReviewCells2020
The Path towards Predicting Evolution as Illustrated in Yeast Cell Polarity.
Review in Cells, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Global genetic rewiring during compensatory evolution in the yeast polarity network.EMBO reports · 2026Article
- Oligomerization-dependent and synergistic regulation of Cdc42 GTPase cycling by a GEF and a GAP.EMBO reports · 2026Article
- Redundancy and the role of protein copy numbers in the cell polarization machinery of budding yeast.Nature communications · 2023Article
- Symmetry Breaking as an Interdisciplinary Concept Unifying Cell and Developmental Biology.Cells · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A bottom-up route towards predicting evolution relies on a deep understanding of the complex network that proteins form inside cells. In a rapidly expanding panorama of experimental possibilities, the most difficult question is how to conceptually approach the disentangling of such complex networks. These can exhibit varying degrees of hierarchy and modularity, which obfuscate certain protein functions that may prove pivotal for adaptation. Using the well-established polarity network in budding yeast as a case study, we first organize current literature to highlight protein entrenchments inside polarity. Following three examples, we see how alternating between experimental novelties and subsequent emerging design strategies can construct a layered understanding, potent enough to reveal evolutionary targets. We show that if you want to understand a cell's evolutionary capacity, such as possible future evolutionary paths, seemingly unimportant proteins need to be mapped and studied. Finally, we generalize this research structure to be applicable to other systems of interest.
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Registered trials
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