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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

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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...
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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.
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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Related Experiment Video

Updated: Jun 23, 2026

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
08:35

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

Pomelo II: finding differentially expressed genes.

Edward R Morrissey1, Ramón Diaz-Uriarte

  • 1Structural and Computational Biology Programme, Spanish National Cancer Center (CNIO), Melchor FernA!ndez Almagro 3, Madrid, 28029, Spain.

Nucleic Acids Research
|May 14, 2009
PubMed
Summary
This summary is machine-generated.

Pomelo II is a free, open-source bioinformatics tool for analyzing gene expression and tissue array data. It offers advanced statistical methods and parallel computing for complex biological data analysis.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Gene expression and tissue array data analysis are crucial for understanding biological processes.
  • Existing tools may lack flexibility for complex experimental designs or efficient computation.

Purpose of the Study:

  • To introduce Pomelo II, a versatile, open-source web-based tool for analyzing gene and protein expression and tissue array data.
  • To provide advanced statistical functionalities and efficient computation for biological data analysis.

Main Methods:

  • Implementation of permutation-based tests (t-test, ANOVA, regression), Cox survival analysis, and Fisher's exact test.
  • Utilization of linear models with empirical Bayes moderated statistics and support for additional covariates.
  • Application of parallel computing for permutation-based and Cox model analyses on multicore CPUs and clusters.

Main Results:

  • Pomelo II integrates diverse statistical analyses for gene expression and tissue array data.
  • The tool supports complex experimental designs through the inclusion of additional covariates.
  • Parallel computing enhances the efficiency of computationally intensive analyses.

Conclusions:

  • Pomelo II is a unique, freely available tool offering advanced statistical methods and parallel computing for biological data analysis.
  • Its open-source nature and comprehensive testing suite ensure flexibility, reusability, and reliability.
  • The tool facilitates access to integrated biological annotations for deeper insights into gene functions and pathways.