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

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
Epistasis Analysis01:09

Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
Combinatorial Gene Control02:33

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

You might also read

Related Articles

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

Sort by
Same author

Health system learning enables generalist neuroimaging models.

Nature medicine·2026
Same author

Integrated proteogenomic and metabolomic profiling of acute myeloid leukemias to identify molecular subtypes and associated therapy targets.

Nature cancer·2026
Same author

Translational bottlenecks in blood-based proteomics.

EMBO molecular medicine·2026
Same author

Lipidomic Predictors of Paclitaxel-Induced Peripheral Neuropathy.

JCO precision oncology·2026
Same author

VO: The Vaccine Ontology.

Scientific data·2026
Same author

A 15-layer multi-omics analysis of gastric cancer ecotypes provides therapeutic insights.

Cell reports. Medicine·2026

Related Experiment Video

Updated: Jun 17, 2026

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

ConceptGen: a gene set enrichment and gene set relation mapping tool.

Maureen A Sartor1, Vasudeva Mahavisno, Venkateshwar G Keshamouni

  • 1Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA. sartorma@umich.edu

Bioinformatics (Oxford, England)
|December 17, 2009
PubMed
Summary

ConceptGen is a new tool for analyzing gene expression data. It helps researchers explore biological concepts and relationships, offering novel visualizations for genomic data interpretation.

More Related Videos

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Genome-Wide CRISPR Screen for Unveiling Radiosensitive and Radioresistant Genes
08:32

Genome-Wide CRISPR Screen for Unveiling Radiosensitive and Radioresistant Genes

Published on: May 23, 2025

Related Experiment Videos

Last Updated: Jun 17, 2026

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Genome-Wide CRISPR Screen for Unveiling Radiosensitive and Radioresistant Genes
08:32

Genome-Wide CRISPR Screen for Unveiling Radiosensitive and Radioresistant Genes

Published on: May 23, 2025

Area of Science:

  • Genomics
  • Bioinformatics
  • Systems Biology

Background:

  • Analyzing genomic data requires understanding biological concepts and gene expression.
  • Exploring relationships between biological concepts from diverse sources is crucial.
  • Existing tools lack unified frameworks for data agglomeration and novel visualizations.

Purpose of the Study:

  • To develop a user-friendly web-based tool for gene set enrichment and gene set relation mapping.
  • To integrate diverse biological knowledge and provide novel visualization capabilities.
  • To facilitate the interpretation of complex genomic data.

Main Methods:

  • Developed ConceptGen, a web-based platform.
  • Integrated over 20,000 concepts from 14 types of biological knowledge.
  • Implemented novel visualizations for exploring gene set relationships.

Main Results:

  • ConceptGen provides streamlined gene set enrichment and relation mapping.
  • The tool includes unique biological data not found in other platforms.
  • Demonstrated functionality with gene expression data (TGF-beta EMT) and prostate cancer metabolomics data.

Conclusions:

  • ConceptGen offers a unified framework for genomic data analysis.
  • The tool enhances the exploration of biological concepts and their relationships.
  • ConceptGen simplifies the interpretation of complex biological datasets through visualization.