Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

What are Lipids?

What are Lipids?

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Deep Learning-Based Electrocardiogram Analysis for Pulmonary Embolism Diagnosis: A Systematic Review and Meta-Analysis.

Acta Cardiologica Sinica·2026

Same author

Pulmonary infarction mimicking pneumonia in Sjögren's syndrome.

The American journal of medicine·2026

Same author

Baseline ¹<sup>8</sup>F-FDG PET/CT radiomics predict early progression and survival in small cell lung cancer.

BMC cancer·2026

Same author

ImmiR: A database of microRNAs associated with immune checkpoints and infiltrates.

Computational and structural biotechnology journal·2025

Same author

Integrative multi-omics and preclinical analyses identify miR-4776-5p as a prognostic radiosensitizer for patients undergoing radiotherapy for head-and-neck cancer.

Discover oncology·2025

Same author

MTAP deficiency confers resistance to cytosolic nucleic acid sensing and STING agonists.

Science (New York, N.Y.)·2025

Same journal

Region-aware bridge modeling enables interpretable mesoscale representation of spatial transcriptomic tissue sections.

Bioinformatics advances·2026

Same journal

Microbiome differential abundance methodologies to detect relevant taxa associated with chemotherapy toxicity rate in colorectal cancer.

Bioinformatics advances·2026

Same journal

maldipickr dereplicates microbial MALDI-TOF spectra to facilitate multiplexed isolation.

Bioinformatics advances·2026

Same journal

RAM-MSA: an anytime memory-bounded method for exact multiple sequence alignment using path finding.

Bioinformatics advances·2026

Same journal

Interpretable machine learning for low-sample multi-omics: a case study of ferret vaccine response.

Bioinformatics advances·2026

Same journal

DeepTaxa: a hybrid CNN-BERT framework for 16S rRNA taxonomic classification.

Bioinformatics advances·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 21, 2025

Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Published on: March 8, 2020

LipidSigR: a R-based solution for integrated lipidomics data analysis and visualization.

Chia-Hsin Liu¹, Pei-Chun Shen¹, Meng-Hsin Tsai¹

¹Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.

Bioinformatics Advances

|March 20, 2025

Summary

This summary is machine-generated.

LipidSigR, an R package, enhances lipidomics data analysis by offering a flexible, open-source tool for customized workflows. This addresses limitations of the LipidSig web platform for researchers.

More Related Videos

Shotgun Lipidomics of Rodent Tissues

Shotgun Lipidomics of Rodent Tissues

Published on: November 18, 2022

Author Spotlight: Unraveling the Pathogenesis of Age-Related Macular Degeneration and Discovering Potential Therapies

Author Spotlight: Unraveling the Pathogenesis of Age-Related Macular Degeneration and Discovering Potential Therapies

Published on: July 28, 2023

Related Experiment Videos

Last Updated: May 21, 2025

Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Published on: March 8, 2020

Shotgun Lipidomics of Rodent Tissues

Shotgun Lipidomics of Rodent Tissues

Published on: November 18, 2022

Author Spotlight: Unraveling the Pathogenesis of Age-Related Macular Degeneration and Discovering Potential Therapies

Author Spotlight: Unraveling the Pathogenesis of Age-Related Macular Degeneration and Discovering Potential Therapies

Published on: July 28, 2023

Area of Science:

Lipidomics
Bioinformatics
Computational Biology

Background:

Lipidomics is a growing field requiring advanced tools for complex data analysis.
Existing platforms like LipidSig offer valuable lipidomics data analysis but have workflow customization limitations.

Purpose of the Study:

To develop a flexible, open-source R package, LipidSigR, as a companion to the LipidSig web platform.
To enable researchers to build customized lipidomics data analysis workflows.

Main Methods:

Developed LipidSigR as an R package based on the existing LipidSig web platform's code.
Ensured compatibility and reproducibility through rigorous testing following CRAN guidelines.
Demonstrated functionality using a common case-control experimental design in lipidomics.

Main Results:

LipidSigR provides enhanced flexibility for adapting lipidomics workflows.
The package allows researchers with basic R skills to customize data analysis pipelines.
A case study illustrates the practical application and capabilities of LipidSigR for lipidomics research.

Conclusions:

LipidSigR is a valuable, freely available resource for the lipidomics community.
The R package empowers researchers to create tailored data analysis workflows, advancing the field.
LipidSigR promotes reproducible and adaptable lipidomics data analysis.