Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

11.8K
Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
11.8K
Cancer Survival Analysis01:21

Cancer Survival Analysis

329
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...
329
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

5.7K
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,...
5.7K
Tumor Progression02:07

Tumor Progression

6.2K
Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
6.2K
Cancer Stem Cells and Tumor Maintenance02:40

Cancer Stem Cells and Tumor Maintenance

4.9K
Early diagnosis and treatment can often cure cancer. However, even with treatment, residual cells called cancer stem cells (CSC) might remain, often causing tumor recurrence. These cancer stem cells possess the potential for self-renewal and multi-lineage differentiation and are often responsible for the therapeutic resistance displayed in most cancers.
Cancer stem cells are thought to originate from tissue-specific normal stem cells or progenitor cells. The normal stem cells usually reside in...
4.9K
Cancer02:18

Cancer

48.1K
Cancers arise due to mutations in genes involved in the regulation of cell division, which leads to unrestricted cell proliferation. Modern science and medicine have made great strides in the understanding and treatment of cancer, including eradicating cancer in some patients. However, there is still no cure for cancer. This is largely due to the fact that cancer is a large group of many diseases.
48.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Exploring Intratumor Heterogeneity in Cancer: A Comparative Evaluation of Clustering Methods.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same author

Exploring the Influence of Gene Networks on Driver Gene Classification.

Journal of computational biology : a journal of computational molecular cell biology·2025
See all related articles

Related Experiment Video

Updated: Jun 12, 2025

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma
15:07

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

Published on: December 28, 2015

26.6K

Analysis of clonal evolution in cancer: A computational perspective.

Paulo Henrique Ribeiro1, Adenilso Simao2

  • 1Federal Institute of São Paulo & University of São Paulo, Barretos & São Carlos, SP, Brazil.

Journal of Bioinformatics and Computational Biology
|June 10, 2025
PubMed
Summary

Understanding cancer clonal evolution is key. This paper details computational methods for analyzing tumor cell populations and their genetic mutations, aiding cancer genomics research.

Keywords:
Clonal evolutioncomputational methodsdriver mutations

More Related Videos

Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

6.7K
Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
07:49

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Published on: April 18, 2025

116

Related Experiment Videos

Last Updated: Jun 12, 2025

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma
15:07

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

Published on: December 28, 2015

26.6K
Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

6.7K
Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
07:49

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Published on: April 18, 2025

116

Area of Science:

  • Oncology
  • Computational Biology
  • Genomics

Background:

  • Cancer progresses via Darwinian evolution of cells with genetic mutations, leading to tumor clonal evolution.
  • Identifying tumor clonal structure from genetic sequencing data is a major challenge in cancer genomics.
  • Existing computational methods for clonal evolution analysis often lack detailed algorithmic explanations.

Purpose of the Study:

  • To provide a detailed computational explanation of algorithms used for cancer clonal evolution analysis.
  • To enhance understanding of the mechanisms behind computational methods for analyzing tumor heterogeneity.
  • To make these computational tools accessible to researchers via an online platform.

Main Methods:

  • Detailed computational explanations of algorithms for clonal evolution analysis.
  • Focus on the algorithmic perspective of computational methods.
  • Implementation of selected methods on an online platform for user accessibility.

Main Results:

  • A clear, computational-level exposition of key algorithms for clonal evolution analysis.
  • An accessible online platform enabling researchers to run and adapt these methods.
  • Improved understanding of the computational underpinnings of cancer genomics analysis.

Conclusions:

  • Detailed computational insights into cancer clonal evolution analysis methods are crucial.
  • Accessible computational tools facilitate research in cancer genomics and tumor heterogeneity.
  • The developed platform empowers researchers to apply and customize advanced analytical methods.