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

RNA-seq03:21

RNA-seq

10.5K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
10.5K

You might also read

Related Articles

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

Sort by
Same author

An Optimization Method of Production-Distribution in Multi-Value-Chain.

Sensors (Basel, Switzerland)·2023
Same author

LILRB2-containing small extracellular vesicles from glioblastoma promote tumor progression by promoting the formation and expansion of myeloid-derived suppressor cells.

Cancer immunology, immunotherapy : CII·2023
Same author

Pure endoscopic minimally invasive surgery with a non‑expandable tubular retractor for intradural extramedullary spinal tumors.

Experimental and therapeutic medicine·2023
Same author

Stable Expression of dmiR-283 in the Brain Promises Positive Effects in Endurance Exercise on Sleep-Wake Behavior in Aging <i>Drosophila</i>.

International journal of molecular sciences·2023
Same author

Endoscopic endonasal transsphenoidal approach for craniopharyngioma: A case report.

Experimental and therapeutic medicine·2023
Same author

MorphoSim: an efficient and scalable phase-field framework for accurately simulating multicellular morphologies.

NPJ systems biology and applications·2023

Related Experiment Video

Updated: Oct 7, 2025

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing
09:49

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing

Published on: July 5, 2019

9.7K

Sequence Fusion Algorithm of Tumor Gene Sequencing and Alignment Based on Machine Learning.

Chao Tang1, Ling Luo2, Yu Xu3

  • 1Radiation & Cancer Biology Laboratory, Radiation Oncology Center, Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital & Chongqing Cancer, Institute & Chongqing Cancer Hospital, Chongqing 400030, China.

Computational Intelligence and Neuroscience
|January 10, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces machine learning and sparse matrix methods for accurate DNA sequence variation detection, crucial for identifying disease-related mutations in tumor gene testing. The proposed fusion method improves detection accuracy and recall rates, especially with increasing data depth.

More Related Videos

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
11:02

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

Published on: October 18, 2013

19.6K
Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

6.9K

Related Experiment Videos

Last Updated: Oct 7, 2025

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing
09:49

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing

Published on: July 5, 2019

9.7K
Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
11:02

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

Published on: October 18, 2013

19.6K
Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

6.9K

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput DNA sequencing reveals strong links between genetic variations and human diseases.
  • Accurate detection of rare DNA sequence variations, particularly Single Nucleotide Polymorphisms (SNPs) and Insertions/Deletions (InDels), is vital for disease gene testing.
  • Existing mutation detection software exhibits discrepancies, leading to errors in sequence comparison and mutation identification.

Purpose of the Study:

  • To develop and evaluate novel methods for SNP and InDel detection using machine learning and sparse matrix approaches.
  • To compare the performance of the proposed methods against established tools like VarScan 2, GATK, BCFtools, and FreeBayes.
  • To enhance the accuracy and efficiency of tumor gene testing through improved variation detection.

Main Methods:

  • Implementation of machine learning algorithms for SNP and InDel detection.
  • Development of a DNA sequence sparse matrix for rapid variation point detection and reasoning.
  • Comparative analysis of proposed methods with VarScan 2, Genome Analysis Toolkit (GATK), BCFtools, and FreeBayes.
  • Evaluation of detection accuracy and recall rates at varying sequencing depths.

Main Results:

  • The proposed machine learning and sparse matrix-based methods demonstrate improved performance in SNP and InDel detection.
  • Detection accuracy and recall rates were observed to increase with higher sequencing data depth.
  • The novel reasoning fusion method showed advantages in comparative analysis and discovery of SNPs and InDels.
  • The approach proved effective for detecting variations in genes associated with swelling and pain.

Conclusions:

  • The developed machine learning and sparse matrix detection methods offer a robust approach for identifying DNA sequence variations.
  • The reasoning fusion technique enhances the reliability and discovery potential of mutation detection.
  • This study provides a valuable tool for advancing tumor gene testing and understanding disease-associated genetic variations.