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Related Concept Videos

Cell Specific Gene Expression01:58

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
Cell Specific Gene Expression01:58

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
Organization of Genes02:07

Organization of Genes

Overview
Organization of Genes02:07

Organization of Genes

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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.
Structure of a Gene01:30

Structure of a Gene

A gene is the fundamental unit of heredity. Every individual has two copies of each gene, one inherited from each parent. Although most people contain the same genes, there is a small fraction that is slightly different amongst people. A gene with a small difference in its sequence of DNA bases forms different alleles, contributing to different phenotypes.
However, only 1% of the DNA is composed of genes that encode proteins; the rest, 99% is non-coding DNA. This non-coding DNA performs...

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Related Experiment Video

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Defining Gene Functions in Tumorigenesis by Ex vivo Ablation of Floxed Alleles in Malignant Peripheral Nerve Sheath Tumor Cells
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GO-2D: identifying 2-dimensional cellular-localized functional modules in Gene Ontology.

Jing Zhu1, Jing Wang, Zheng Guo

  • 1Department of Bioinformatics, Harbin Medical University, Harbin 150086, China. jingzhu@ems.hrbmu.edu.cn <jingzhu@ems.hrbmu.edu.cn>

BMC Genomics
|January 26, 2007
PubMed
Summary

GO-2D identifies 2-dimensional functional modules by combining Gene Ontology (GO) categories for a deeper understanding of complex human diseases. This approach refines biological processes with cellular locations, revealing specific disease-relevant insights.

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Area of Science:

  • Bioinformatics
  • Systems Biology
  • Genomics

Background:

  • High-throughput biotechnologies generate vast gene expression data.
  • Understanding complex human diseases requires functional module analysis.
  • Existing tools primarily use one-dimensional functional analysis based on Gene Ontology (GO).

Purpose of the Study:

  • To develop a novel tool, GO-2D, for identifying two-dimensional functional modules.
  • To enhance the functional interpretation of high-throughput microarray data.
  • To uncover cellular-localized functional modules relevant to complex diseases.

Main Methods:

  • Developed GO-2D, a tool integrating combined GO categories.
  • Refined biological process categories by incorporating cellular component information.
  • Identified enriched combined categories using differentially expressed genes.

Main Results:

  • GO-2D successfully identified specific, disease-relevant processes by incorporating cellular location.
  • Analysis of two human cancer datasets demonstrated the utility of the 2D approach.
  • The tool extracts functionally compact and detailed modules.

Conclusions:

  • GO-2D provides a powerful two-dimensional approach for disease-gene association studies.
  • Characterizing disease modules by biological processes and cellular locations offers deeper insights.
  • This 2D method complements existing 1D approaches for identifying disease-relevant modules.