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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.
Genomics02:02

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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...
Gene Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...
Gene Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...
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...

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Related Experiment Video

Updated: Jun 25, 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

A general modular framework for gene set enrichment analysis.

Marit Ackermann1, Korbinian Strimmer

  • 1Biotechnology Center, Technical University Dresden, 01062 Dresden, Germany.

BMC Bioinformatics
|February 5, 2009
PubMed
Summary
This summary is machine-generated.

Gene set enrichment analysis (GSEA) methods are crucial for genomic studies. This research unifies various GSEA approaches into a general framework, aiding in method selection and understanding their performance.

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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
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Last Updated: Jun 25, 2026

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Published on: August 16, 2017

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

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Area of Science:

  • Genomics
  • Bioinformatics
  • Statistical analysis

Background:

  • Gene set enrichment analysis (GSEA) is increasingly vital for interpreting high-throughput genomic data.
  • Numerous statistical methods exist for GSEA, but their relationships and comparative performance remain unclear.

Purpose of the Study:

  • To survey statistical approaches for gene set analysis.
  • To propose a unifying framework for GSEA.
  • To provide a meta-theory for understanding and comparing GSEA methods.

Main Methods:

  • Extensive survey of existing gene set analysis statistical approaches.
  • Identification of a common modular structure across methods.
  • Development of a general framework for gene set enrichment detection.

Main Results:

  • A common modular structure was identified in most published GSEA methods.
  • The proposed framework facilitates understanding, comparison, and insights into method interplay.
  • Computer simulations compared 261 GSEA variants.

Conclusions:

  • The developed framework aids in understanding the relative merits of different GSEA procedures.
  • Analysis of experimental datasets and simulations provide recommendations for best practices in GSEA.
  • Principled comparison of gene set enrichment procedures is enabled by the framework.