ReviewWiley interdisciplinary reviews. Systems biology and medicine2016
Computational modeling approaches to the dynamics of oncolytic viruses.
Review in Wiley interdisciplinary reviews. Systems biology and medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Shaping viral immunotherapy towards cancer-targeted immunological cell death.Frontiers in oncology · 2025Review
- Article
- Applications of Intravital Imaging in Cancer Immunotherapy.Bioengineering (Basel, Switzerland) · 2024Review
- Agent-Based and Continuum Models for Spatial Dynamics of Infection by Oncolytic Viruses.Bulletin of mathematical biology · 2023Article
- Article
- Towards a Mathematical Model for the Viral Progression in the Pharynx.Healthcare (Basel, Switzerland) · 2021Article
- Oncolytic viruses encoding bispecific T cell engagers: a blueprint for emerging immunovirotherapies.Journal of hematology & oncology · 2021Review
- Fighting Cancer with Mathematics and Viruses.Viruses · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Replicating oncolytic viruses represent a promising treatment approach against cancer, specifically targeting the tumor cells. Significant progress has been made through experimental and clinical studies. Besides these approaches, however, mathematical models can be useful when analyzing the dynamics of virus spread through tumors, because the interactions between a growing tumor and a replicating virus are complex and nonlinear, making them difficult to understand by experimentation alone. Mathematical models have provided significant biological insight into the field of virus dynamics, and similar approaches can be adopted to study oncolytic viruses. The review discusses this approach and highlights some of the challenges that need to be overcome in order to build mathematical and computation models that are clinically predictive. WIREs Syst Biol Med 2016, 8:242-252. doi: 10.1002/wsbm.1332 For further resources related to this article, please visit the WIREs website.
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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.