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Related Concept Videos

What are Lipids?01:38

What are Lipids?

Overview
What are Lipids?01:31

What are Lipids?

Lipids function as structural components of cellular membranes, in addition to acting as energy reservoirs and signaling molecules. They are thus crucial to all living organisms.  The three biologically important classes of lipids are triglycerides, phospholipids, and steroids.
Non-Polar and Hydrophobic Characteristics of Lipids
Lipids are a structurally and functionally diverse group of hydrocarbons—compounds consisting of carbon and hydrogen atoms. The carbon-carbon and carbon-hydrogen bonds...
What are Lipids?01:31

What are Lipids?

Lipids function as structural components of cellular membranes, in addition to acting as energy reservoirs and signaling molecules. They are thus crucial to all living organisms.  The three biologically important classes of lipids are triglycerides, phospholipids, and steroids.
Non-Polar and Hydrophobic Characteristics of Lipids
Lipids are a structurally and functionally diverse group of hydrocarbons—compounds consisting of carbon and hydrogen atoms. The carbon-carbon and carbon-hydrogen bonds...
What are Lipids?01:38

What are Lipids?

Overview
Lipids as Anchors01:32

Lipids as Anchors

In the plasma membrane, the lipids forming the bilayer can also act as an anchor to tether proteins to the membrane. The three main types of lipid anchors found in eukaryotes are – prenyl groups, fatty acyl groups, and glycosylphosphatidylinositol or GPI groups. Prenyl and fatty acyl groups act as anchors on the cytosolic surface of the membrane, whereas GPI anchors proteins on the extracellular side.
The carboxy-terminal of most of the prenylated proteins, such as Ras proteins, contains the...
Biosynthesis of Lipids01:29

Biosynthesis of Lipids

Microbial membranes exhibit remarkable diversity in lipid composition, reflecting evolutionary adaptations to various environmental conditions. The three domains of life—Bacteria, Archaea, and Eukarya—synthesize membrane lipids through distinct biosynthetic pathways, leading to fundamental structural differences that impact membrane stability, function, and adaptability.Fatty Acid-Based Lipids in Bacteria and EukaryaBacteria and eukaryotes share a common fatty acid biosynthesis pathway, which...

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Updated: May 21, 2026

Isolation of Lipoprotein Particles from Chicken Egg Yolk for the Study of Bacterial Pathogen Fatty Acid Incorporation into Membrane Phospholipids
11:59

Isolation of Lipoprotein Particles from Chicken Egg Yolk for the Study of Bacterial Pathogen Fatty Acid Incorporation into Membrane Phospholipids

Published on: May 15, 2019

Eigenlipids for exploring lipid biology.

Nicholas Sing1, Adam Alexander T Smith2, Aleksandar Dakic3

  • 1Metabolomics Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; Department of Mathematical and Physical Sciences La Trobe University, Melbourne, VIC, Australia; Department of Cardiovascular Research Translation and Implementation, La Trobe University, Melbourne, VIC, Australia.

Journal of Lipid Research
|May 19, 2026
PubMed
Summary
This summary is machine-generated.

Eigenlipids simplify complex lipidomics data by identifying key lipid patterns. This review explores their generation, application in lipid biology, and future methodological advancements for better biological insights.

Keywords:
Bioinformaticseigengeneeigenlipideigenmetabolitelipid modelinglipid modellinglipidomicslipidslipid•metabolomics

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SNARE-mediated Fusion of Single Proteoliposomes with Tethered Supported Bilayers in a Microfluidic Flow Cell Monitored by Polarized TIRF Microscopy
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Published on: August 24, 2016

Defining Substrate Specificities for Lipase and Phospholipase Candidates
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Defining Substrate Specificities for Lipase and Phospholipase Candidates

Published on: November 23, 2016

Related Experiment Videos

Last Updated: May 21, 2026

Isolation of Lipoprotein Particles from Chicken Egg Yolk for the Study of Bacterial Pathogen Fatty Acid Incorporation into Membrane Phospholipids
11:59

Isolation of Lipoprotein Particles from Chicken Egg Yolk for the Study of Bacterial Pathogen Fatty Acid Incorporation into Membrane Phospholipids

Published on: May 15, 2019

SNARE-mediated Fusion of Single Proteoliposomes with Tethered Supported Bilayers in a Microfluidic Flow Cell Monitored by Polarized TIRF Microscopy
10:58

SNARE-mediated Fusion of Single Proteoliposomes with Tethered Supported Bilayers in a Microfluidic Flow Cell Monitored by Polarized TIRF Microscopy

Published on: August 24, 2016

Defining Substrate Specificities for Lipase and Phospholipase Candidates
08:59

Defining Substrate Specificities for Lipase and Phospholipase Candidates

Published on: November 23, 2016

Area of Science:

  • Lipidomics
  • Systems Biology
  • Bioinformatics

Background:

  • Lipidomics studies analyze thousands of lipids, often showing high correlations due to metabolic pathways.
  • Eigenlipids, adapted from transcriptomics, can represent these complex lipid associations.
  • Differences in data structure between gene expression and lipidomics require specific analytical considerations.

Purpose of the Study:

  • To review the generation and application of eigenlipids in lipidomics.
  • To discuss the utility of eigenlipids in exploring lipid-phenotype relationships.
  • To highlight potential pitfalls and future methodological developments in eigenlipid analysis.

Main Methods:

  • Review of existing literature on eigenlipid generation and application.
  • Discussion of data structure considerations for lipidomics vs. transcriptomics.
  • Exploration of dimensionality reduction techniques for eigenlipid analysis.

Main Results:

  • Eigenlipids offer a method to reduce dimensionality and capture key lipid associations.
  • Their application aids in understanding lipid metabolism and biological relationships.
  • Potential pitfalls include misinterpretation due to data structure differences.

Conclusions:

  • Eigenlipids are a valuable tool for analyzing complex lipidomics data.
  • Further methodological development is needed for optimal application.
  • Future directions include exploring alternative dimensionality reduction and targeted eigenlipid generation.