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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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Multi-input and Multi-variable systems01:22

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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
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Synthetic Biology02:55

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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.
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Proteomics01:33

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Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
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Related Experiment Video

Updated: Oct 16, 2025

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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Defining NASH from a Multi-Omics Systems Biology Perspective.

Lili Niu1,2, Karolina Sulek1,3, Catherine G Vasilopoulou2

  • 1Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark.

Journal of Clinical Medicine
|October 23, 2021
PubMed
Summary

Multi-omics analysis offers new insights into non-alcoholic steatohepatitis (NASH) pathogenesis by integrating proteomic, metabolomic, and lipidomic data. This approach aids in discovering novel biomarkers for this complex liver disease.

Keywords:
NAFLDbiomarker discoveryliver diseasemachine learningmulti-omicssystems biology

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Area of Science:

  • Hepatology and Molecular Biology
  • Biomarker Discovery
  • Systems Biology

Background:

  • Non-alcoholic steatohepatitis (NASH) is a prevalent chronic liver disease with unclear molecular mechanisms.
  • Current diagnostic criteria rely on histologic features like steatosis and inflammation.
  • Single omics studies have identified potential biomarkers but lack comprehensive mechanistic insights.

Purpose of the Study:

  • To review recent technological advancements in mass spectrometry-based omics.
  • To summarize multi-omics studies investigating NASH.
  • To highlight emerging omics biomarkers and biological insights in NASH.

Main Methods:

  • Review of mass spectrometry (MS)-based proteomics, metabolomics, and lipidomics technologies.
  • Synthesis of findings from multi-omics studies in NASH research.
  • Analysis of integrated omics data for biomarker identification.

Main Results:

  • Multi-omics approaches provide a more integrated understanding of NASH pathogenesis compared to single omics.
  • Emerging omics biomarkers show promise for improved NASH diagnosis and monitoring.
  • Technological advancements in MS are enhancing the scope and depth of omics analyses.

Conclusions:

  • Multi-omics integration is crucial for unraveling the complex molecular mechanisms of NASH.
  • Further research utilizing advanced omics technologies can lead to better diagnostic and therapeutic strategies for NASH.
  • The review underscores the potential of integrated omics data in advancing NASH research.