ReviewWiley interdisciplinary reviews. Systems biology and medicine
In silico models of cancer.
Review in Wiley interdisciplinary reviews. Systems biology and medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 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
49 citing papers in PubMed.
- Exploring the role of EMT in ovarian cancer progression using a multiscale mathematical model.NPJ systems biology and applications · 2025Article
- Advancing cancer drug development with mechanistic mathematical modeling: bridging the gap between theory and practice.Journal of pharmacokinetics and pharmacodynamics · 2024Review
- Application of liposomal nanoparticles of berberine in photodynamic therapy of A549 lung cancer spheroids.Biochemistry and biophysics reports · 2024Article
- Unveiling the potential anti-cancer activity of calycosin against multivarious cancers with molecular insights: A promising frontier in cancer research.Cancer medicine · 2024Review
- Integrative genomic analyses combined with molecular dynamics simulations reveal the impact of deleterious mutations of Bcl-2 gene on the apoptotic machinery and implications in carcinogenesis.Frontiers in genetics · 2024Article
- Antiproliferative and Apoptosis Effects of Hybrid Varieties of Vitis vinifera L. Sweet Sapphire and Sweet Surprise on Human Prostate Cancer Cells Using In Vitro and In Silico Approaches.Asian Pacific journal of cancer prevention : APJCP · 2023Article
- Hybrid computational models of multicellular tumour growth considering glucose metabolism.Computational and structural biotechnology journal · 2023Review
- Three-dimensional in vitro culture models in oncology research.Cell & bioscience · 2022Review
- Article
- An Early Stage Researcher's Primer on Systems Medicine Terminology.Network and systems medicine · 2021Review
- Modeling of Nanotherapy Response as a Function of the Tumor Microenvironment: Focus on Liver Metastasis.Frontiers in bioengineering and biotechnology · 2020Review
- Time-lapse imaging of HeLa spheroids in soft agar culture provides virtual inner proliferative activity.PloS one · 2020Article
- Mathematical modeling of tumor-immune cell interactions.Journal of theoretical biology · 2019Review
- Upcoming Revolutionary Paths in Preclinical Modeling of Pancreatic Adenocarcinoma.Frontiers in oncology · 2019Review
- Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment.Processes (Basel, Switzerland) · 2019Article
- The Multitarget Activity of Natural Extracts on Cancer: Synergy and Xenohormesis.Medicines (Basel, Switzerland) · 2018Review
- Simulation of Multispecies Desmoplastic Cancer Growth via a Fully Adaptive Non-linear Full Multigrid Algorithm.Frontiers in physiology · 2018Article
- Quantitative Characterization of CD8+ T Cell Clustering and Spatial Heterogeneity in Solid Tumors.Frontiers in oncology · 2018Article
- A HYBRID THREE-SCALE MODEL OF TUMOR GROWTH.Mathematical models & methods in applied sciences : M3AS · 2018Article
- The biology and mathematical modelling of glioma invasion: a review.Journal of the Royal Society, Interface · 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
3 authors.
Funding
Abstract
Cancer is a complex disease that involves multiple types of biological interactions across diverse physical, temporal, and biological scales. This complexity presents substantial challenges for the characterization of cancer biology, and motivates the study of cancer in the context of molecular, cellular, and physiological systems. Computational models of cancer are being developed to aid both biological discovery and clinical medicine. The development of these in silico models is facilitated by rapidly advancing experimental and analytical tools that generate information-rich, high-throughput biological data. Statistical models of cancer at the genomic, transcriptomic, and pathway levels have proven effective in developing diagnostic and prognostic molecular signatures, as well as in identifying perturbed pathways. Statistically inferred network models can prove useful in settings where data overfitting can be avoided, and provide an important means for biological discovery. Mechanistically based signaling and metabolic models that apply a priori knowledge of biochemical processes derived from experiments can also be reconstructed where data are available, and can provide insight and predictive ability regarding the behavior of these systems. At longer length scales, continuum and agent-based models of the tumor microenvironment and other tissue-level interactions enable modeling of cancer cell populations and tumor progression. Even though cancer has been among the most-studied human diseases using systems approaches, significant challenges remain before the enormous potential of in silico cancer biology can be fully realized.
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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.