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

DNA Microarrays02:34

DNA Microarrays

17.2K
Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
17.2K

You might also read

Related Articles

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

Sort by
Same author

Adapting clinical chemistry plasma as a source for liquid biopsies.

eLife·2026
Same author

Sequencing of Pleural Fluid and Plasma for Tuberculous Pleuritis.

NEJM evidence·2026
Same author

Adapting Clinical Chemistry Plasma as a Source for Liquid Biopsies.

medRxiv : the preprint server for health sciences·2026
Same author

Holistic determination of ends of cfDNA molecules.

Cell genomics·2026
Same author

Checking Up on the King of Cancers.

Cancer discovery·2026
Same author

Cell-free DNA in 2030.

Med (New York, N.Y.)·2026
Same journal

A unified analysis of cell type- and trajectory-associated pathways in single-cell data using Phoenix.

Genome research·2026
Same journal

Resf1 is required for proper placental development and configuration of trophoblast cell-specific heterochromatin.

Genome research·2026
Same journal

Telomere-driven replicative crisis is driven by large-scale changes in genomic architecture.

Genome research·2026
Same journal

Spatially informed reference-free cell-type deconvolution for spatial transcriptomics with SpatialCD.

Genome research·2026
Same journal

Spatially resolved profiling of steroid nuclear receptors reveals a role for the disordered N-terminal domains in genome targeting and AP-1 interaction.

Genome research·2026
Same journal

Flexible and scalable inference of spatially varying correlation in spatial transcriptomics with spCorr.

Genome research·2026
See all related articles

Related Experiment Video

Updated: May 31, 2025

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

661

Artificial intelligence and machine learning in cell-free-DNA-based diagnostics.

W H Adrian Tsui1,2,3, Spencer C Ding1,2,3, Peiyong Jiang1,2,3,4

  • 1Center for Novostics, Hong Kong Science Park, Pak Shek Kok, New Territories, Hong Kong SAR, China.

Genome Research
|January 22, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) and machine learning (ML) are revolutionizing liquid biopsy by analyzing cell-free DNA (cfDNA) fragmentation patterns. These technologies enhance noninvasive diagnostics for prenatal testing and cancer detection.

More Related Videos

Cell-Free Dot Blot as a Practical and Adaptable Immunoassay Platform for the Detection of Antibody Response in Human and Animal Sera
08:21

Cell-Free Dot Blot as a Practical and Adaptable Immunoassay Platform for the Detection of Antibody Response in Human and Animal Sera

Published on: May 23, 2025

119
In vitro Assembly of Semi-artificial Molecular Machine and its Use for Detection of DNA Damage
08:56

In vitro Assembly of Semi-artificial Molecular Machine and its Use for Detection of DNA Damage

Published on: January 11, 2012

11.6K

Related Experiment Videos

Last Updated: May 31, 2025

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

661
Cell-Free Dot Blot as a Practical and Adaptable Immunoassay Platform for the Detection of Antibody Response in Human and Animal Sera
08:21

Cell-Free Dot Blot as a Practical and Adaptable Immunoassay Platform for the Detection of Antibody Response in Human and Animal Sera

Published on: May 23, 2025

119
In vitro Assembly of Semi-artificial Molecular Machine and its Use for Detection of DNA Damage
08:56

In vitro Assembly of Semi-artificial Molecular Machine and its Use for Detection of DNA Damage

Published on: January 11, 2012

11.6K

Area of Science:

  • Genomics and Bioinformatics
  • Computational Biology
  • Molecular Diagnostics

Background:

  • Circulating cell-free DNA (cfDNA) in plasma offers noninvasive diagnostic potential for fetal aneuploidies, cancer detection, and transplant monitoring.
  • High-throughput sequencing enables detailed analysis of cfDNA characteristics, yielding numerous biomarkers across genetics, epigenetics, transcriptomics, and fragmentomics.
  • Machine learning (ML) and artificial intelligence (AI) excel at integrating high-dimensional data, making them suitable for advancing liquid biopsy applications.

Purpose of the Study:

  • To review and highlight various AI and ML approaches applied to cfDNA-based diagnostics.
  • To discuss the integration of ML/AI with cfDNA analysis for noninvasive prenatal testing and cancer liquid biopsy.
  • To explore future directions for leveraging cfDNA fragmentation patterns using ML/AI in methylomic and transcriptional investigations.

Main Methods:

  • Introduction to the biology of cfDNA and fundamental concepts of ML and AI technologies.
  • Discussion of selected ML/AI-based applications in cfDNA diagnostics, including noninvasive prenatal testing and cancer liquid biopsy.
  • Analysis of specific applications such as fetal DNA fraction deduction, plasma DNA tissue mapping, and cancer detection/localization.

Main Results:

  • AI and ML effectively analyze cfDNA characteristics, enhancing the precision of noninvasive diagnostic tests.
  • Applications demonstrated include accurate fetal DNA fraction determination and improved cancer detection and localization through liquid biopsy.
  • cfDNA fragmentomics, combined with ML/AI, shows promise for future diagnostic advancements in epigenetics and transcriptomics.

Conclusions:

  • AI and ML are powerful tools for advancing cfDNA-based liquid biopsy, offering significant improvements in noninvasive diagnostics.
  • The integration of ML/AI with cfDNA analysis holds great potential for early disease detection, risk assessment, and personalized medicine.
  • Future research should focus on further developing ML/AI algorithms to fully exploit cfDNA fragmentation patterns for comprehensive diagnostic insights.