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Related Concept Videos

Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...
Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
Diversity in Cell Signaling Responses01:22

Diversity in Cell Signaling Responses

The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity. 
Graded and Abrupt Responses
Some signaling systems generate...

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Related Experiment Video

Updated: May 11, 2026

Cancer-Associated Fibroblasts from Mouse Mammary Tumors as Tools for Molecular and Computational Studies
09:01

Cancer-Associated Fibroblasts from Mouse Mammary Tumors as Tools for Molecular and Computational Studies

Published on: July 3, 2025

Dealing with diversity in computational cancer modeling.

David Johnson1, Steve McKeever, Georgios Stamatakos

  • 1Department of Computer Science, University of Oxford, Oxford, UK.

Cancer Informatics
|May 24, 2013
PubMed
Summary
This summary is machine-generated.

Interconnecting computational cancer models enhances accuracy and speeds clinical translation. Developing cancer-specific XML markup is key for integrating diverse models in predictive oncology.

Keywords:
XML markup languagesin silico oncologymodel interoperabilitymulti-scale computational tumor modeling

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Published on: September 19, 2019

Area of Science:

  • Computational biology
  • Translational oncology
  • Bioinformatics

Background:

  • Current computational cancer models lack integration across different sources and scales.
  • Interoperability is crucial for accelerating the clinical adaptation and validation of predictive oncology models.
  • Existing European Commission Virtual Physiological Human projects highlight the need for in silico model integration.

Purpose of the Study:

  • To discuss the necessity of interconnecting computational cancer models for clinical relevance.
  • To review current interoperability efforts in predictive oncology.
  • To propose XML-based solutions for coupling diverse cancer models.

Main Methods:

  • Review of existing interoperability initiatives in computational cancer modeling.
  • Case study of a clinically relevant brain tumor modeling scenario.
  • Exploration of XML-based markup languages for biological modeling.

Main Results:

  • Interconnecting models from various sources and scales improves accuracy and clinical translation.
  • A brain tumor modeling scenario exemplifies the need for multi-scale model coupling.
  • XML-based approaches offer a viable path toward model interoperability.

Conclusions:

  • Standardized, cancer-specific XML markup is essential for coupling component models.
  • Enhanced interoperability will facilitate predictive in silico oncology.
  • Integrated computational models promise to advance personalized cancer care.