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Related Concept Videos

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-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
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,...

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Related Experiment Video

Updated: May 30, 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

[Identification, modeling and simulation of key pathways underlying certain cancers].

Hao Guo1, Yun-Ping Zhu, Dong Li

  • 1State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 100850, China. haosmail@gmail.com

Yi Chuan = Hereditas
|August 12, 2011
PubMed
Summary

This review explores algorithms and models for identifying and simulating tumor biological pathways using microarray data. It highlights current challenges and future directions in cancer research.

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Generation of High-Throughput Three-Dimensional Tumor Spheroids for Drug Screening
05:54

Generation of High-Throughput Three-Dimensional Tumor Spheroids for Drug Screening

Published on: September 5, 2018

Related Experiment Videos

Last Updated: May 30, 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

Generation of High-Throughput Three-Dimensional Tumor Spheroids for Drug Screening
05:54

Generation of High-Throughput Three-Dimensional Tumor Spheroids for Drug Screening

Published on: September 5, 2018

Area of Science:

  • Oncology
  • Bioinformatics
  • Systems Biology

Context:

  • Cancer's complexity necessitates understanding biological pathways in tumorigenesis, progression, and metastasis.
  • Microarray data analysis is crucial for identifying and simulating these tumor-related pathways.
  • Numerous algorithms and models have been developed to analyze large-scale gene expression datasets.

Purpose:

  • To review recent advancements in algorithms and models for pathway identification and simulation.
  • To provide a comprehensive list of relevant software and data sources.
  • To discuss existing challenges and future perspectives in the field of cancer pathway analysis.

Summary:

  • This paper reviews computational approaches for analyzing microarray data to identify and simulate biological pathways involved in cancer.
  • It covers algorithms, models, software, and data sources, offering insights into the current state of the field.
  • The review also addresses limitations and outlines future research directions for understanding cancer mechanisms.

Impact:

  • Facilitates a deeper understanding of cancer mechanisms through pathway analysis.
  • Supports the development of novel diagnostic and therapeutic strategies by identifying key biological pathways.
  • Provides researchers with a valuable resource for navigating the complex landscape of cancer bioinformatics tools and data.