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Related Concept Videos

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...
DNA Microarrays02:34

DNA Microarrays

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...
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...
Proteomics01:33

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...
Synthetic Biology02:55

Synthetic Biology

Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...

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Related Experiment Video

Updated: May 8, 2026

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease
08:51

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

Published on: September 20, 2024

A modular framework for gene set analysis integrating multilevel omics data.

Steffen Sass1, Florian Buettner, Nikola S Mueller

  • 1Institute of Computational Biology, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany and Department of Mathematics, Technische Universität München, Boltzmannstraße 3, 85747 Garching, Germany.

Nucleic Acids Research
|August 27, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a new Bayesian method, Multi-level ONtology Analysis (MONA), for integrated multi-omics data analysis. MONA significantly improves biological interpretation compared to single-omics approaches, even with complex regulatory interactions.

Related Experiment Videos

Last Updated: May 8, 2026

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease
08:51

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

Published on: September 20, 2024

Area of Science:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • High-throughput technologies enable multi-omics data generation (mRNA, protein, DNA methylation, microRNA).
  • Understanding cellular responses requires integrating diverse omics data for mechanistic insights.
  • Existing methods struggle to analyze combined data types effectively.

Purpose of the Study:

  • To develop a novel method for analyzing integrated multi-omics data.
  • To simultaneously assess the biological meaning across multiple omics levels.
  • To improve upon conventional single-omics analysis techniques.

Main Methods:

  • Developed a model-based Bayesian method for inferring term probabilities.
  • Implemented a modular framework for flexible analysis.
  • Introduced the Multi-level ONtology Analysis (MONA) algorithm.

Main Results:

  • MONA demonstrated significantly superior performance compared to analyses of individual omics levels.
  • The algorithm achieved optimal results even with complex models, including microRNA-mediated mRNA regulation.
  • The framework accommodates various regulatory motifs and ontologies.

Conclusions:

  • MONA provides a robust and flexible approach for integrated multi-omics data analysis.
  • The method enhances biological interpretation by considering multiple data types simultaneously.
  • MONA is a ready-to-use tool for researchers, available as a standalone application.