ArticleCell2025
Human interpretable grammar encodes multicellular systems biology models to democratize virtual cell laboratories.
Article in Cell, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 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
30 citing papers in PubMed.
- Artificial intelligence virtual bone organoids (AIVBOs).Journal of orthopaedic translation · 2026Review
- Topologically-based parameter inference for agent-based model selection from spatiotemporal cellular data.PLoS computational biology · 2026Article
- Interpreting Pulmonary Hypertension Beyond Single Cells.Arteriosclerosis, thrombosis, and vascular biology · 2026Article
- A Hierarchical Multimodal Knowledge Graph for Neural Cell-Type-Specific Regulation Integrating Single-Cell Transcriptomics and Literature Evidence.International journal of molecular sciences · 2026Article
- Cancer-Associated Fibroblasts Promote Epithelial-Mesenchymal Transition and Classical to Basal Subtype Shift in Pancreatic Cancer.Cancer research · 2026Article
- Preclinical and Virtual Models of Mucosal Melanoma: Bridging Translational Gaps in a Rare and Lethal Cancer.Pigment cell & melanoma research · 2026Review
- Intelligent tool orchestration for rapid mechanistic model prototyping: MCP servers as AI-biology interfaces.NPJ systems biology and applications · 2026Article
- Digital twins to accelerate target identification and drug development for immune-mediated disorders.FEBS open bio · 2026Review
- Article
- Multiscale predictive cellular modeling: integrating hypothesis grammars, digital twins, and multi-omics for In silico oncology and precision theranostics.Functional & integrative genomics · 2026Review
- A Guide for Spatial Omics Technologies: Innovation, Evaluation, and Application.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Beyond the Cell Atlas: Functional Communities as the Essential Pathologic Units Driving Kidney Disease.Journal of the American Society of Nephrology : JASN · 2026Review
- Tumor-immune trajectory context connects static tissue architecture to clinical outcomes.bioRxiv : the preprint server for biology · 2026Article
- Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in Pancreatic Cancer.bioRxiv : the preprint server for biology · 2026Article
- Mapping multipathology via spatial omic integration.Current opinion in biotechnology · 2026Review
- Data driven network inference and longitudinal transcriptomics unveil dynamic regulation in Chronic Lymphocytic Leukaemia models.NPJ systems biology and applications · 2026Article
- A Phenotype-Structured PDE Framework for Investigating the Role of Hypoxic Memory on Tumor Invasion under Cyclic Hypoxia.Bulletin of mathematical biology · 2026Article
- Mathematical modeling of combinatorial antigen targeting with multiple CAR T-cell products for glioblastoma treatment.NPJ systems biology and applications · 2026Article
- Drug-loaded nanoparticles for cancer therapy: A high-throughput multicellular agent-based modeling study.Journal of theoretical biology · 2026Article
- Trajectory Landscapes for Therapeutic Strategy Design in Agent-Based Tumor Microenvironment Models.IEEE control systems letters · 2026Article
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Authors and funding
47 authors.
Funding
Abstract
Cells interact as dynamically evolving ecosystems. While recent single-cell and spatial multi-omics technologies quantify individual cell characteristics, predicting their evolution requires mathematical modeling. We propose a conceptual framework-a cell behavior hypothesis grammar-that uses natural language statements (cell rules) to create mathematical models. This enables systematic integration of biological knowledge and multi-omics data to generate in silico models, enabling virtual "thought experiments" that test and expand our understanding of multicellular systems and generate new testable hypotheses. This paper motivates and describes the grammar, offers a reference implementation, and demonstrates its use in developing both de novo mechanistic models and those informed by multi-omics data. We show its potential through examples in cancer and its broader applicability in simulating brain development. This approach bridges biological, clinical, and systems biology research for mathematical modeling at scale, allowing the community to predict emergent multicellular behavior.
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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.