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

Viral Recombination00:57

Viral Recombination

24.8K
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.
24.8K
Protein Networks02:26

Protein Networks

4.4K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.4K
Introduction to Virus01:28

Introduction to Virus

1.1K
Viruses are unique biological entities that blur the boundary between living and non-living systems. Although they lack cellular structure and metabolic processes, they can exhibit characteristics of life when infecting a host. Their defining feature is a nucleic acid core, composed of either DNA or RNA, encapsulated within a protein coat called a capsid. This simple structure allows them to invade host cells and use their machinery for replication efficiently.Viral Structure and...
1.1K

You might also read

Related Articles

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

Sort by
Same author

Activation of the Nrf2 pathway by inorganic arsenic in human hepatocytes and the role of transcriptional repressor Bach1.

Oxidative medicine and cellular longevity·2013
Same author

Simultaneous Quantification of Limonin, Two Indolequinazoline Alkaloids, and Four Quinolone Alkaloids in Evodia rutaecarpa (Juss.) Benth by HPLC-DAD Method.

Journal of analytical methods in chemistry·2013
Same author

Ten-eleven translocation 1 (Tet1) is regulated by O-linked N-acetylglucosamine transferase (Ogt) for target gene repression in mouse embryonic stem cells.

The Journal of biological chemistry·2013
Same author

BAD overexpression inhibits cell growth and induces apoptosis via mitochondrial-dependent pathway in non-small cell lung cancer.

Cancer cell international·2013
Same author

Cigarette smoking is associated with human semen quality in synergy with functional NRF2 polymorphisms.

Biology of reproduction·2013
Same author

Downregulation of Erbin in Her2-overexpressing breast cancer cells promotes cell migration and induces trastuzumab resistance.

Molecular immunology·2013

Related Experiment Video

Updated: Jan 2, 2026

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions
13:56

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Published on: July 18, 2013

11.5K

Predicting virus-host association by Kernelized logistic matrix factorization and similarity network fusion.

Dan Liu1,2, Yingjun Ma1,2, Xingpeng Jiang3,4

  • 1School of Computer, Central China Normal University, Wuhan, Hubei, China.

BMC Bioinformatics
|December 3, 2019
PubMed
Summary

Predicting virus-host associations is crucial for understanding microbial communities. Our novel method, ILMF-VH, integrates network information to accurately identify potential viral hosts, improving upon existing techniques.

Keywords:
Gaussian interaction profileLogistic matrix factorizationOligonucleotide frequencySimilarity network fusionVirus-host association

More Related Videos

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

2.0K
Purification of Viral DNA for the Identification of Associated Viral and Cellular Proteins
08:26

Purification of Viral DNA for the Identification of Associated Viral and Cellular Proteins

Published on: August 31, 2017

14.1K

Related Experiment Videos

Last Updated: Jan 2, 2026

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions
13:56

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Published on: July 18, 2013

11.5K
A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

2.0K
Purification of Viral DNA for the Identification of Associated Viral and Cellular Proteins
08:26

Purification of Viral DNA for the Identification of Associated Viral and Cellular Proteins

Published on: August 31, 2017

14.1K

Area of Science:

  • Microbiology
  • Computational Biology
  • Bioinformatics

Background:

  • Viruses play a significant role in human diseases and microbial community dynamics.
  • Accurate virus-host association prediction is essential for understanding these complex interactions.
  • Existing methods often overlook the known virus-host association network.

Purpose of the Study:

  • To develop an effective computational tool for predicting virus-host associations.
  • To integrate diverse information sources for improved prediction accuracy.
  • To discover novel virus-host interactions.

Main Methods:

  • Proposed a kernelized logistic matrix factorization method (ILMF-VH).
  • Constructed a heterogeneous network by integrating virus and host networks based on known associations.
  • Developed virus and host networks using oligonucleotide frequency and similarity network fusion.

Main Results:

  • ILMF-VH demonstrated superior host prediction accuracy compared to other methods.
  • Case studies validated the method's ability to predict known virus-host associations.
  • Identified potential novel hosts for viruses, including crAssphage and Escherichia coli.

Conclusions:

  • ILMF-VH is an effective computational tool for predicting virus-host interactions.
  • The method shows significant potential for discovering novel viral hosts.
  • This approach enhances our understanding of virus-host dynamics in microbial ecosystems.