ArticleMethods in molecular biology (Clifton, N.J.)2018
An Introduction to Computational Modeling of Cardiac Electrophysiology and Arrhythmogenicity.
Article in Methods in molecular biology (Clifton, N.J.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- A Machine Learning Pipeline to Screen Large In Vivo Molecular Data to Curate Disease Signatures of High Translational Potential.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Article
- Modeling Human Cardiac Arrhythmias: Insights from Zebrafish.Journal of cardiovascular development and disease · 2022Review
- Model Systems for Addressing Mechanism of Arrhythmogenesis in Cardiac Repair.Current cardiology reports · 2021Review
- Review
- Does the Heart Want What It Wants? A Case for Self-Adapting, Mechano-Sensitive Therapies After Infarction.Frontiers in cardiovascular medicine · 2021Article
- Review
- Article
- Limitations of Animal Studies for Predicting Toxicity in Clinical Trials: Part 2: Potential Alternatives to the Use of Animals in Preclinical Trials.JACC. Basic to translational science · 2020Article
- Exploring cardiac form and function: A length-scale computational biology approach.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
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 modeling is a powerful tool to study the complex and orchestrated biological process of cardiac electrical activity. By integrating experimental data from key components of cardiac electrophysiology, systems biology simulations can complement empirical findings, provide quantitative insight into physiological and pathophysiological mechanisms of action, and guide new hypotheses to better understand this complex biological system to develop novel cardiotherapeutic approaches. In this chapter, we briefly introduce in silico methods to describe the dynamics of physiological and pathophysiological single-cell and tissue-level cardiac electrophysiology. Using a "bottom-up" approach, we first describe the basis of ion channel mathematical models. Next, we discuss how the net flux of ions through such channels leads to changes in transmembrane voltage during cardiomyocyte action potentials. By applying these fundamentals, we describe how action potentials propagate in models of cardiac tissue. In addition, we provide case studies simulating single-cell and tissue-level arrhythmogenesis, as well as promising approaches to circumvent or overcome such adverse events. Overall, basic concepts and tools are discussed in this chapter as an accessible introduction to nonmathematicians to foster an understanding of electrophysiological modeling studies and help facilitate communication with dry lab colleagues and collaborators.
Indexed as
Identifiers
What Socratic 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 Socratic graph.