ReviewCurrent pathobiology reports2020
Leveraging Computational Modeling to Understand Infectious Diseases.
Review in Current pathobiology reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed.
- Review
- New nicotinamide-thiadiazol hybrids as VEGFR-2 inhibitors for breast cancer therapy: design, synthesis andRSC advances · 2025Article
- The EpiFusion Analysis Framework for joint phylodynamic and epidemiological analysis of outbreak characteristics.F1000Research · 2025Article
- Clinical management and burden of cytomegalovirus in D+/R-Kidney transplant recipients in Canada.Frontiers in immunology · 2025Article
- Bioinformatics and molecular biology tools for diagnosis, prevention, treatment and prognosis of COVID-19.Heliyon · 2024Review
- NIAID/SMB Workshop on Multiscale Modeling of Infectious and Immune-Mediated Diseases.Bulletin of mathematical biology · 2024Article
- Digital Twins of Biological Systems: A Narrative Review.IEEE open journal of engineering in medicine and biology · 2024Article
- Tensor-based insights into systems immunity and infectious disease.Trends in immunology · 2023Article
- Natural Products as a Potential Source of Promising Therapeutics for COVID-19 and Viral Diseases.Evidence-based complementary and alternative medicine : eCAM · 2023Review
- Determining the rate of infectious disease testing through contagion potential.PLOS global public health · 2023Article
- Analytical mapping of information and communication technology in emerging infectious diseases using CiteSpace.Telematics and informatics · 2022Review
- Multiscale Model of Antiviral Timing, Potency, and Heterogeneity Effects on an Epithelial Tissue Patch Infected by SARS-CoV-2.Viruses · 2022Article
- Integrative lymph node-mimicking models created with biomaterials and computational tools to study the immune system.Materials today. Bio · 2022Review
- Article
- Systems biology approaches to investigate the role of granulomas in TB-HIV coinfection.Frontiers in immunology · 2022Review
- Quantifying dose-, strain-, and tissue-specific kinetics of parainfluenza virus infection.PLoS computational biology · 2021Article
- Modeling transmission of pathogens in healthcare settings.Current opinion in infectious diseases · 2021Review
- COVID-19 virtual patient cohort suggests immune mechanisms driving disease outcomes.PLoS pathogens · 2021Article
- A multi-method approach to modeling COVID-19 disease dynamics in the United States.Scientific reports · 2021Article
- COVID-19 virtual patient cohort reveals immune mechanisms driving disease outcomes.bioRxiv : the preprint server for biology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
purpose of reviewComputational and mathematical modeling have become a critical part of understanding in-host infectious disease dynamics and predicting effective treatments. In this review, we discuss recent findings pertaining to the biological mechanisms underlying infectious diseases, including etiology, pathogenesis, and the cellular interactions with infectious agents. We present advances in modeling techniques that have led to fundamental disease discoveries and impacted clinical translation. RECENT
findingsCombining mechanistic models and machine learning algorithms has led to improvements in the treatment of SUMMARY: Computational modeling is now more than ever at the forefront of infectious disease research due to the COVID-19 pandemic. This review highlights how infectious diseases can be better understood by connecting scientists from medicine and molecular biology with those in computer science and applied mathematics.
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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.