ReviewLife sciences2014
Mathematical modeling of physiological systems: an essential tool for discovery.
Review in Life sciences, 2014. 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
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
11 citing papers in PubMed.
- Molecular Pathways and Animal Models of Arrhythmias.Advances in experimental medicine and biology · 2024Article
- Article
- Defining new mechanistic roles for αII spectrin in cardiac function.The Journal of biological chemistry · 2019Article
- Protein Phosphatase 2A Regulates Cardiac NaCirculation research · 2019Article
- A computational model to understand mouse iron physiology and disease.PLoS computational biology · 2019Article
- A mathematical model of COIntensive care medicine experimental · 2018Article
- Potassium currents in the heart: functional roles in repolarization, arrhythmia and therapeutics.The Journal of physiology · 2017Review
- Rabbit models of cardiac mechano-electric and mechano-mechanical coupling.Progress in biophysics and molecular biology · 2016Review
- Article
- Modeling Lymph Flow and Fluid Exchange with Blood Vessels in Lymph Nodes.Lymphatic research and biology · 2015Article
- Applying Biotechnology and Bioengineering to Pediatric Lung Disease: Emerging Paradigms and Platforms.Frontiers in pediatrics · 2015Review
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
Mathematical models are invaluable tools for understanding the relationships between components of a complex system. In the biological context, mathematical models help us understand the complex web of interrelations between various components (DNA, proteins, enzymes, signaling molecules etc.) in a biological system, gain better understanding of the system as a whole, and in turn predict its behavior in an altered state (e.g. disease). Mathematical modeling has enhanced our understanding of multiple complex biological processes like enzyme kinetics, metabolic networks, signal transduction pathways, gene regulatory networks, and electrophysiology. With recent advances in high throughput data generation methods, computational techniques and mathematical modeling have become even more central to the study of biological systems. In this review, we provide a brief history and highlight some of the important applications of modeling in biological systems with an emphasis on the study of excitable cells. We conclude with a discussion about opportunities and challenges for mathematical modeling going forward. In a larger sense, the review is designed to help answer a simple but important question that theoreticians frequently face from interested but skeptical colleagues on the experimental side: "What is the value of a model?"
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.