ArticleFrontiers in immunology2023
Data driven model discovery and interpretation for CAR T-cell killing using sparse identification and latent variables.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- The future of mathematical oncology in the age of AI.NPJ systems biology and applications · 2026Review
- Data-driven computational modeling of CAR-T cell function.Frontiers in immunology · 2026Article
- Navigating the landscape of personalized oncology: overcoming challenges and expanding horizons with computational modeling.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Mathematical Oncology: How Modeling Is Transforming Clinical Decision-Making.Cancer research · 2025Review
- CAR T-cell and oncolytic virus dynamics and determinants of combination therapy success for glioblastoma.Mathematical biosciences · 2025Article
- Modeling Adoptive Cell Therapy in Bladder Cancer from Sparse Biological Data using PINNs.ArXiv · 2025Article
- Implicit Runge-Kutta based sparse identification of governing equations in biologically motivated systems.Scientific reports · 2025Article
- Spatiotemporal dynamics of tumor-CAR T-cell interaction following local administration in solid cancers.PLoS computational biology · 2025Article
- Mathematical modeling unveils the timeline of CAR-T cell therapy and macrophage-mediated cytokine release syndrome.PLoS computational biology · 2025Article
- Mathematical models and computational approaches in CAR-T therapeutics.Frontiers in immunology · 2025Review
- Data-driven model discovery and model selection for noisy biological systems.PLoS computational biology · 2025Article
- DataXflow: Synergizing data-driven modeling with best parameter fit and optimal control - An efficient data analysis for cancer research.Computational and structural biotechnology journal · 2024Article
- Article
- Model discovery approach enables noninvasive measurement of intra-tumoral fluid transport in dynamic MRI.APL bioengineering · 2024Article
- From biological data to oscillator models using SINDy.iScience · 2024Article
- Designing clinical trials for patients who are not average.iScience · 2024Review
- A review of mechanistic learning in mathematical oncology.Frontiers in immunology · 2024Review
- Model-informed drug development of autologous CAR-T cell therapy: Strategies to optimize CAR-T cell exposure leveraging cell kinetic/dynamic modeling.CPT: pharmacometrics & systems pharmacology · 2023Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
In the development of cell-based cancer therapies, quantitative mathematical models of cellular interactions are instrumental in understanding treatment efficacy. Efforts to validate and interpret mathematical models of cancer cell growth and death hinge first on proposing a precise mathematical model, then analyzing experimental data in the context of the chosen model. In this work, we present the first application of the sparse identification of non-linear dynamics (SINDy) algorithm to a real biological system in order discover cell-cell interaction dynamics in
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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.