ArticleeLife2025
De novo identification of universal cell mechanics gene signatures.
Article in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The trial behind it
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Who cites it
11 citing papers in PubMed.
- Deformability screening identifies NUDT5 as a mediator of cellular mechanobiology.bioRxiv : the preprint server for biology · 2026Article
- High-throughput mechanomic screening reveals novel regulators of single-cell mechanics.Biophysical journal · 2026Article
- Review
- High-throughput Genome Wide CRISPR Knock Out mechanical sort identifies genes driving metastatic cancer cell softening.bioRxiv : the preprint server for biology · 2026Article
- Genome-scale metabolic modelling of the priority fungal pathogenmicroLife · 2026Article
- Computational prediction of cellular elastic modulus from mechanosensitive gene expression at multiple biological levels.BioData mining · 2025Article
- A computational pipeline for spatial mechano-transcriptomics.Nature methods · 2025Article
- Programming the elongation of mammalian cell aggregates with synthetic gene circuits.bioRxiv : the preprint server for biology · 2024Article
- Spatial Reconstruction of Oligo and Single Cells by De Novo Coalescent Embedding of Transcriptomic Networks.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Understanding How Cells Probe the World: A Preliminary Step towards Modeling Cell Behavior?International journal of molecular sciences · 2023Article
- Image-based cell sorting using focused travelling surface acoustic waves.Lab on a chip · 2023Article
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
Cell mechanical properties determine many physiological functions, such as cell fate specification, migration, or circulation through vasculature. Identifying factors that govern the mechanical properties is therefore a subject of great interest. Here, we present a mechanomics approach for establishing links between single-cell mechanical phenotype changes and the genes involved in driving them. We combine mechanical characterization of cells across a variety of mouse and human systems with machine learning-based discriminative network analysis of associated transcriptomic profiles to infer a conserved network module of five genes with putative roles in cell mechanics regulation. We validate in silico that the identified gene markers are universal, trustworthy, and specific to the mechanical phenotype across the studied mouse and human systems, and demonstrate experimentally that a selected target,
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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.