ReviewAnnual review of biomedical engineering2013
Multiscale computational models of complex biological systems.
Review in Annual review of biomedical engineering, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
107 citing papers in PubMed.
- Process bigraphs and the architecture of compositional systems biology.PLoS computational biology · 2026Article
- Multiscale computational modeling to quantify how spiral artery remodeling alters wall shear stress on placental villi.PLoS computational biology · 2026Article
- Multiscale modelling of birth-death processes.Journal of mathematical biology · 2026Article
- Virtual cell: Current perspectives and future prospects.The Journal of international medical research · 2026Review
- Matters of life and death in computational cell biology.NPJ systems biology and applications · 2026Review
- Experimentally calibrated multiscale model predicts schedule dependent drug combination effects.NPJ systems biology and applications · 2026Article
- Agent-based modeling of cellular dynamics in adoptive cell therapy.Communications biology · 2026Article
- Viability and prediction of encapsulated Trichoderma spp. isolates using machine learning: a multi-layer perceptron-based approach.Archives of microbiology · 2026Article
- Article
- scMultiNODE: Integrative and Scalable Framework for Multi-Modal Temporal Single-Cell Data.bioRxiv : the preprint server for biology · 2025Article
- Temporal and spatial omics technologies for 4D profiling.Nature methods · 2025Review
- Multi-scale modeling and simulation of skeletal muscles with different fatigue degrees based on microphysiology.Scientific reports · 2025Article
- Challenges and opportunities for digital twins in precision medicine from a complex systems perspective.NPJ digital medicine · 2025Review
- Acoustic immune reprogramming: a novel paradigm for spatiotemporally controlled immune regulation using ultrasound-responsive nanoplatforms.Frontiers in immunology · 2025Review
- Multiscale computational model predicts how environmental changes and treatments affect microvascular remodeling in fibrotic disease.PNAS nexus · 2025Article
- Agent-based modeling in cancer biomedicine: applications and tools for calibration and validation.Cancer biology & therapy · 2024Review
- Foundations of a Compositional Systems Biology.ArXiv · 2024Article
- Mathematical Modeling and Inference of Epidermal Growth Factor-Induced Mitogen-Activated Protein Kinase Cell Signaling Pathways.International journal of molecular sciences · 2024Review
- Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics.International journal of molecular sciences · 2024Review
- In Silico Electrophysiological Investigation of Transient Receptor Potential Melastatin-4 Ion Channel Biophysics to Study Detrusor Overactivity.International journal of molecular sciences · 2024Article
47 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Integration of data across spatial, temporal, and functional scales is a primary focus of biomedical engineering efforts. The advent of powerful computing platforms, coupled with quantitative data from high-throughput experimental methodologies, has allowed multiscale modeling to expand as a means to more comprehensively investigate biological phenomena in experimentally relevant ways. This review aims to highlight recently published multiscale models of biological systems, using their successes to propose the best practices for future model development. We demonstrate that coupling continuous and discrete systems best captures biological information across spatial scales by selecting modeling techniques that are suited to the task. Further, we suggest how to leverage these multiscale models to gain insight into biological systems using quantitative biomedical engineering methods to analyze data in nonintuitive ways. These topics are discussed with a focus on the future of the field, current challenges encountered, and opportunities yet to be realized.
Indexed as
Identifiers
What OpenQuestion holds
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.