ArticleCell2024
Machine learning interpretable models of cell mechanics from protein images.
Article in Cell, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed, 50 citations in OpenAlex.
- Nuclear mechanotransduction: tools for mechanical perturbation and chromatin characterization.Nucleus (Austin, Tex.) · 2026Review
- Interpretable biophysical neural networks of transcriptional activation domains separate roles of protein abundance and coactivator binding.Cell systems · 2026Article
- From pixels to patterns: the AI revolution in stem cell-derived models.Nature methods · 2026Review
- Elevated contractility drives implantation failure in mouse embryos from aged females.Nature cell biology · 2026Article
- Vascular Smooth Muscle Myosin 2 Filaments Dynamically Assemble and Stabilize During Induced Contractility.Arteriosclerosis, thrombosis, and vascular biology · 2026Article
- Living Inorganic Nanomaterials: Design, Preparation, and Biomedical Applications.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Cell shapes decode molecular phenotypes in image-based spatial proteomics.Cell systems · 2026Article
- Article
- Local RhoA activation induces anillin-independent septin recruitment in interphase cells.Molecular biology of the cell · 2026Article
- Vascular Smooth Muscle Myosin 2 Filaments Dynamically Assemble and Stabilize During Induced Contractility.bioRxiv : the preprint server for biology · 2026Article
- Machine learning multiscale collective cell dynamics: From single-cell characterization to multicellular monolayer modeling.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Topological control of spontaneous failure in active nematic solids.Nature materials · 2026Article
- Double Sided Traction Force Microscopy: A Method to Confine Cells for Physiologically Relevant Force Measurements.Cytoskeleton (Hoboken, N.J.) · 2026Article
- Monocytes are biological sensors of aging and frailty in humans.bioRxiv : the preprint server for biology · 2026Article
- Dynamic Temporal Modeling of Abdominal Aortic Aneurysm Morphology with Z-SINDy.medRxiv : the preprint server for health sciences · 2026Article
- Trans-scale bioimaging and integrative biology: on the debut of China National Biomedical Imaging Center.Science China. Life sciences · 2025Article
- A mechanical origin for implantation defects in embryos from aged females.bioRxiv : the preprint server for biology · 2025Article
- Local RhoA activation induces septin recruitment.bioRxiv : the preprint server for biology · 2025Article
- Interpretable biophysical neural networks of transcriptional activation domains separate roles of protein abundance and coactivator binding.bioRxiv : the preprint server for biology · 2025Article
- Sociohydrodynamics: Data-driven modeling of social behavior.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
Cellular form and function emerge from complex mechanochemical systems within the cytoplasm. Currently, no systematic strategy exists to infer large-scale physical properties of a cell from its molecular components. This is an obstacle to understanding processes such as cell adhesion and migration. Here, we develop a data-driven modeling pipeline to learn the mechanical behavior of adherent cells. We first train neural networks to predict cellular forces from images of cytoskeletal proteins. Strikingly, experimental images of a single focal adhesion (FA) protein, such as zyxin, are sufficient to predict forces and can generalize to unseen biological regimes. Using this observation, we develop two approaches-one constrained by physics and the other agnostic-to construct data-driven continuum models of cellular forces. Both reveal how cellular forces are encoded by two distinct length scales. Beyond adherent cell mechanics, our work serves as a case study for integrating neural networks into predictive models for cell biology.
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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.