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Related Concept Videos

Genomics02:02

Genomics

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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...
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What is Gene Expression?01:42

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Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
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DNA Microarrays02:34

DNA Microarrays

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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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Cell Specific Gene Expression01:58

Cell Specific Gene Expression

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Genome-wide Association Studies-GWAS01:11

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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...
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GeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression Analysis.

Mohamed Helmy1,2, Rahul Agrawal3, Javed Ali3

  • 1Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore, Singapore.

Frontiers in Bioinformatics
|October 28, 2022
PubMed
Summary
This summary is machine-generated.

GeneCloudOmics offers an accessible web platform for analyzing complex gene expression data from DNA microarrays and RNA-Sequencing. This tool simplifies bioinformatics tasks for researchers, enabling deeper insights into biological systems.

Keywords:
OMICS dataRNA-seqbioinformaticsdata analyticsgene expression analysismicroarraytranscriptomics

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput gene expression profiling using DNA microarray and RNA-Sequencing is crucial for understanding biological systems across various research areas.
  • Wet experimentalists often face challenges in analyzing and leveraging the complex, large-scale data generated by these techniques.
  • Existing bioinformatics tools may lack comprehensive functionality or user-friendly interfaces for integrated gene expression analysis.

Purpose of the Study:

  • To introduce GeneCloudOmics, an enhanced, user-friendly web server for comprehensive high-throughput gene expression data analysis.
  • To extend the capabilities of the previous ABioTrans tool with new features, including protein dataset analysis and an improved web interface.
  • To provide a unified platform for both microarray and RNA-Seq data analysis, addressing the limitations of current standalone software.

Main Methods:

  • GeneCloudOmics integrates 23 distinct data analytical and bioinformatics tasks, including normalization, correlation, clustering (hierarchical, k-means, t-SNE, SOM), differential expression analysis, pathway enrichment, and protein-protein interaction identification.
  • The platform supports direct data import from the NCBI Gene Expression Omnibus database.
  • It features an intuitive graphical user interface (GUI) designed to eliminate the need for coding, software installation, and operating system compatibility management.

Main Results:

  • GeneCloudOmics provides a comprehensive suite of tools for analyzing both microarray and RNA-Seq data in a single package.
  • The web server facilitates rapid data analysis through its user-friendly GUI, simplifying complex bioinformatics workflows for biologists.
  • Direct integration with the Gene Expression Omnibus database streamlines data acquisition and analysis.

Conclusions:

  • GeneCloudOmics serves as a one-stop, open-source solution for gene expression data analysis and visualization.
  • The platform democratizes access to advanced bioinformatics tools, empowering researchers without extensive computational expertise.
  • It significantly reduces the technical barriers associated with analyzing high-throughput gene expression data, accelerating biological discovery.