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

Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

605
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
605
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.6K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.6K
Velocity and Position by Integral Method01:13

Velocity and Position by Integral Method

8.1K
If acceleration as a function of time is known, then velocity and position functions can be derived using integral calculus. For constant acceleration, the integral equations refer to the first and second kinematic equations for velocity and position functions, respectively.
Consider an example to calculate the velocity and position from the acceleration function. A motorboat is traveling at a constant velocity of 5.0 m/s when it starts to decelerate to arrive at the dock. Its acceleration is...
8.1K
Viral Recombination00:57

Viral Recombination

25.2K
Cells are sometimes infected by more than one virus at once. When two viruses disassemble to expose their genomes for replication in the same cell, similar regions of their genomes can pair together and exchange sequences in a process called recombination. Alternatively, viruses with segmented genomes can swap segments in a process called reassortment.
25.2K
Viral Structure00:56

Viral Structure

74.7K
Viruses are extraordinarily diverse in shape and size, but they all have several structural features in common. All viruses have a core that contains a DNA- or RNA-based genome. The core is surrounded by a protective coat of proteins called the capsid. The capsid is composed of subunits called capsomeres. The capsid and genome-containing core are together known as the nucleocapsid.
74.7K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.8K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
18.8K

You might also read

Related Articles

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

Sort by
Same author

In vitro and in vivo drug release behavior and osteogenic potential of a composite scaffold based on poly(ε-caprolactone)-block-poly(lactic-co-glycolic acid) and β-tricalcium phosphate.

Journal of materials chemistry. B·2020
Same author

Nerve conduits constructed by electrospun P(LLA-CL) nanofibers and PLLA nanofiber yarns.

Journal of materials chemistry. B·2020
Same author

Polypyrrole-coated poly(l-lactic acid-co-ε-caprolactone)/silk fibroin nanofibrous membranes promoting neural cell proliferation and differentiation with electrical stimulation.

Journal of materials chemistry. B·2020
Same author

Laminin-coated nerve guidance conduits based on poly(l-lactide-co-glycolide) fibers and yarns for promoting Schwann cells' proliferation and migration.

Journal of materials chemistry. B·2020
Same author

Upregulation of deubiquitinase PSMD14 in lung adenocarcinoma (LUAD) and its prognostic significance.

Journal of Cancer·2020
Same author

Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks.

Journal of chemical information and modeling·2020

Related Experiment Video

Updated: Feb 6, 2026

Alternative In Vitro Methods for the Determination of Viral Capsid Structural Integrity
12:57

Alternative In Vitro Methods for the Determination of Viral Capsid Structural Integrity

Published on: November 16, 2017

8.7K

Comprehensive comparative analysis of methods and software for identifying viral integrations.

Xun Chen1, Jason Kost1, Dawei Li1,2,3,4

  • 1Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, Vermont 05405, USA.

Briefings in Bioinformatics
|August 14, 2018
PubMed
Summary

This study compares bioinformatics tools for detecting viral DNA integrations in human cancer genomes. Current methods have limitations, highlighting the need for improved virome-wide detection strategies.

Keywords:
method and software comparisonnext-generation sequencing (NGS)oncovirusviral integrationvirome-wide

More Related Videos

Analysis of Group IV Viral SSHHPS Using In Vitro and In Silico Methods
10:40

Analysis of Group IV Viral SSHHPS Using In Vitro and In Silico Methods

Published on: December 21, 2019

26.5K
Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

7.3K

Related Experiment Videos

Last Updated: Feb 6, 2026

Alternative In Vitro Methods for the Determination of Viral Capsid Structural Integrity
12:57

Alternative In Vitro Methods for the Determination of Viral Capsid Structural Integrity

Published on: November 16, 2017

8.7K
Analysis of Group IV Viral SSHHPS Using In Vitro and In Silico Methods
10:40

Analysis of Group IV Viral SSHHPS Using In Vitro and In Silico Methods

Published on: December 21, 2019

26.5K
Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

7.3K

Area of Science:

  • Genomics
  • Virology
  • Bioinformatics
  • Cancer Research

Background:

  • Viral integration into the human genome is a key factor in tumorigenesis.
  • Viral integrations serve as genetic markers for identifying virus-caused cancers and understanding cancer development.
  • Next-generation sequencing (NGS) is crucial for screening viral integrations in cancer genomes.

Purpose of the Study:

  • To systematically compare existing bioinformatics methods and software for detecting viral integrations using NGS data.
  • To evaluate the performance, functionality, and limitations of current viral integration detection tools.
  • To identify strategies for developing comprehensive virome-wide integration detection.

Main Methods:

  • Comprehensive comparative analysis of existing bioinformatics tools for viral integration detection.
  • Evaluation of tool designs, performance, functionality, and limitations.
  • Comparison of sensitivity, precision, and runtime for integration detection using four representative tools.

Main Results:

  • Each analyzed software demonstrated unique strengths but none were adequate for comprehensive virome-wide detection.
  • Significant limitations were identified across existing methods for accurate and parallel viral integration screening.
  • The study provides a critical assessment of current tools' capabilities and shortcomings.

Conclusions:

  • Existing bioinformatics tools for viral integration detection have limitations hindering accurate virome-wide analysis.
  • There is a clear need for the development of improved strategies and tools for comprehensive viral integration detection.
  • This research lays the groundwork for future advancements in detecting viral contributions to cancer.