ArticleCell2025
Contextual computation by competitive protein dimerization networks.
Article in Cell, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Enabling molecular signaling with temperature and ionic-strength independence or programmable dependence.Nature communications · 2026Article
- Programmable DNA-Based Dimerization Networks for Dynamic and Competitive Control of Transcription.Journal of the American Chemical Society · 2026Article
- Combinatorial decision-making driven by multicomponent surface condensates.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- ErbB family receptor dimerization dynamics and dysregulation via long-term single-molecule imaging.Cell · 2026Article
- Transcription factor collaboration enables precise T cell state engineering.bioRxiv : the preprint server for biology · 2026Article
- TGFβ signaling systems are prone to inhibition and ligand competition by coreceptor.bioRxiv : the preprint server for biology · 2026Article
- Protein engineering: status report.Protein engineering, design & selection : PEDS · 2026Review
- Trainable computation in molecular networks.bioRxiv : the preprint server for biology · 2025Article
- Article
- Limits on the computational expressivity of non-equilibrium biophysical processes.Nature communications · 2025Article
- Pattern recognition in living cells through the lens of machine learning.Open biology · 2025Review
- Temporal Contrastive Learning through implicit non-equilibrium memory.Nature communications · 2025Article
- Covalent Dynamic DNA Networks to Translate Multiple Inputs into Programmable Outputs.Journal of the American Chemical Society · 2025Article
Corrections and comments
- Erratum issued
- Update of
Authors and funding
5 authors.
Funding
Abstract
Many biological signaling pathways employ proteins that competitively dimerize in diverse combinations. These dimerization networks can perform biochemical computations in which the concentrations of monomer inputs determine the concentrations of dimer outputs. Despite their prevalence, little is known about the range of input-output computations that dimerization networks can perform and how it depends on network size and connectivity. Using a systematic computational approach, we demonstrate that even small dimerization networks of 3-6 monomers are expressive, performing diverse multi-input computations. Further, dimerization networks are versatile, performing different computations when their protein components are expressed at different levels, such as in different cell types. Remarkably, individual networks with random interaction affinities, when large enough, can perform nearly all potential one-input network computations merely by tuning their monomer expression levels. Thus, even the simple process of competitive dimerization provides a powerful architecture for multi-input, cell-type-specific signal processing.
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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.